Dictionaries, Medical
Dictionaries as Topic
Dictionaries, Chemical
Dictionary
Dictionaries, Pharmaceutic
Terminology as Topic
Dictionaries, Dental
Dictionaries, Polyglot
Dictionaries, Classical
Natural Language Processing
Abstracting and Indexing as Topic
Unified Medical Language System
Names
Information Storage and Retrieval
Encyclopedias as Topic
Artificial Intelligence
Subject Headings
Algorithms
MEDLINE
Pattern Recognition, Automated
Data Mining
Software
Database Management Systems
Physics
Systems Integration
Databases as Topic
Data Compression
Computational Biology
RxNorm
Multilingualism
PubMed
Databases, Protein
Databases, Factual
Systematized Nomenclature of Medicine
Medical Records Systems, Computerized
Internet
Databases, Bibliographic
User-Computer Interface
Proteins
Medical Informatics
Online Systems
Disease
Hospital Information Systems
Documentation
Models, Statistical
Shewanella
Adverse Drug Reaction Reporting Systems
Pharmaceutical Preparations
The CATH Dictionary of Homologous Superfamilies (DHS): a consensus approach for identifying distant structural homologues. (1/73)
A consensus approach has been developed for identifying distant structural homologues. This is based on the CATH Dictionary of Homologous Superfamilies (DHS), a database of validated multiple structural alignments annotated with consensus functional information for evolutionary protein superfamilies (URL: http://www. biochem.ucl.ac.uk/bsm/dhs). Multiple structural alignments have been generated for 362 well-populated superfamilies in the CATH structural domain database and annotated with secondary structure, physicochemical properties, functional sequence patterns and protein-ligand interaction data. Consensus functional information for each superfamily includes descriptions and keywords extracted from SWISS-PROT and the ENZYME database. The Dictionary provides a powerful resource to validate, examine and visualize key structural and functional features of each homologous superfamily. The value of the DHS, for assessing functional variability and identifying distant evolutionary relationships, is illustrated using the pyridoxal-5'-phosphate (PLP) binding aspartate aminotransferase superfamily. The DHS also provides a tool for examining sequence-structure relationships for proteins within each fold group. (+info)Organizing the present, looking to the future: an online knowledge repository to facilitate collaboration. (2/73)
BACKGROUND: Comprehensive data available in the Canadian province of Manitoba since 1970 have aided study of the interaction between population health, health care utilization, and structural features of the health care system. Given a complex linked database and many ongoing projects, better organization of available epidemiological, institutional, and technical information was needed. OBJECTIVE: The Manitoba Centre for Health Policy and Evaluation wished to develop a knowledge repository to handle data, document research Methods, and facilitate both internal communication and collaboration with other sites. METHODS: This evolving knowledge repository consists of both public and internal (restricted access) pages on the World Wide Web (WWW). Information can be accessed using an indexed logical format or queried to allow entry at user-defined points. The main topics are: Concept Dictionary, Research Definitions, Meta-Index, and Glossary. The Concept Dictionary operationalizes concepts used in health research using administrative data, outlining the creation of complex variables. Research Definitions specify the codes for common surgical procedures, tests, and diagnoses. The Meta-Index organizes concepts and definitions according to the Medical Sub-Heading (MeSH) system developed by the National Library of Medicine. The Glossary facilitates navigation through the research terms and abbreviations in the knowledge repository. An Education Resources heading presents a web-based graduate course using substantial amounts of material in the Concept Dictionary, a lecture in the Epidemiology Supercourse, and material for Manitoba's Regional Health Authorities. Confidential information (including Data Dictionaries) is available on the Centre's internal website. RESULTS: Use of the public pages has increased dramatically since January 1998, with almost 6,000 page hits from 250 different hosts in May 1999. More recently, the number of page hits has averaged around 4,000 per month, while the number of unique hosts has climbed to around 400. CONCLUSIONS: This knowledge repository promotes standardization and increases efficiency by placing concepts and associated programming in the Centre's collective memory. Collaboration and project management are facilitated. (+info)The role of definitions in biomedical concept representation. (3/73)
The Foundational Model (FM) of anatomy, developed as an anatomical enhancement of UMLS, classifies anatomical entities in a structural context. Explicit definitions have played a critical role in the establishment of FM classes. Essential structural properties that distinguish a group of anatomical entities serve as the differentiate for defining classes. These, as well as other structural attributes, are introduced as template slots in Protege, a frame-based knowledge acquisition system, and are inherited by descendants of the class. A set of desiderata has evolved during the instantiation of the FM for formulating definitions. We contend that 1. these desiderata generalize to non-anatomical domains and 2. satisfying them in constituent vocabularies of UMLS would enhance the quality of information retrievable through UMLS. (+info)Creating an online dictionary of abbreviations from MEDLINE. (4/73)
OBJECTIVE: The growth of the biomedical literature presents special challenges for both human readers and automatic algorithms. One such challenge derives from the common and uncontrolled use of abbreviations in the literature. Each additional abbreviation increases the effective size of the vocabulary for a field. Therefore, to create an automatically generated and maintained lexicon of abbreviations, we have developed an algorithm to match abbreviations in text with their expansions. DESIGN: Our method uses a statistical learning algorithm, logistic regression, to score abbreviation expansions based on their resemblance to a training set of human-annotated abbreviations. We applied it to Medstract, a corpus of MEDLINE abstracts in which abbreviations and their expansions have been manually annotated. We then ran the algorithm on all abstracts in MEDLINE, creating a dictionary of biomedical abbreviations. To test the coverage of the database, we used an independently created list of abbreviations from the China Medical Tribune. MEASUREMENTS: We measured the recall and precision of the algorithm in identifying abbreviations from the Medstract corpus. We also measured the recall when searching for abbreviations from the China Medical Tribune against the database. RESULTS: On the Medstract corpus, our algorithm achieves up to 83% recall at 80% precision. Applying the algorithm to all of MEDLINE yielded a database of 781,632 high-scoring abbreviations. Of all the abbreviations in the list from the China Medical Tribune, 88% were in the database. CONCLUSION: We have developed an algorithm to identify abbreviations from text. We are making this available as a public abbreviation server at \url[http://abbreviation.stanford.edu/]. (+info)Finding relevant references to genes and proteins in Medline using a Bayesian approach. (5/73)
MOTIVATION: Mining the biomedical literature for references to genes and proteins always involves a tradeoff between high precision with false negatives, and high recall with false positives. Having a reliable method for assessing the relevance of literature mining results is crucial to finding ways to balance precision and recall, and for subsequently building automated systems to analyze these results. We hypothesize that abstracts and titles that discuss the same gene or protein use similar words. To validate this hypothesis, we built a dictionary- and rule-based system to mine Medline for references to genes and proteins, and used a Bayesian metric for scoring the relevance of each reference assignment. RESULTS: We analyzed the entire set of Medline records from 1966 to late 2001, and scored each gene and protein reference using a Bayesian estimated probability (EP) based on word frequency in a training set of 137837 known assignments from 30594 articles to 36197 gene and protein symbols. Two test sets of 148 and 150 randomly chosen assignments, respectively, were hand-validated and categorized as either good or bad. The distributions of EP values, when plotted on a log-scale histogram, are shown to markedly differ between good and bad assignments. Using EP values, recall was 100% at 61% precision (EP=2 x 10(-5)), 63% at 88% precision (EP=0.008), and 10% at 100% precision (EP=0.1). These results show that Medline entries discussing the same gene or protein have similar word usage, and that our method of assessing this similarity using EP values is valid, and enables an EP cutoff value to be determined that accurately and reproducibly balances precision and recall, allowing automated analysis of literature mining results. . (+info)The Protein Data Bank and structural genomics. (6/73)
The Protein Data Bank (PDB; http://www.pdb.org/) continues to be actively involved in various aspects of the informatics of structural genomics projects--developing and maintaining the Target Registration Database (TargetDB), organizing data dictionaries that will define the specification for the exchange and deposition of data with the structural genomics centers and creating software tools to capture data from standard structure determination applications. (+info)Social capital. (7/73)
This glossary aims to provide readers with some of the key terms that are relevant to a consideration of the relevance of social capital for health, and to introduce some of the debates on the concepts. (+info)Extraction of protein interaction information from unstructured text using a context-free grammar. (8/73)
MOTIVATION: As research into disease pathology and cellular function continues to generate vast amounts of data pertaining to protein, gene and small molecule (PGSM) interactions, there exists a critical need to capture these results in structured formats allowing for computational analysis. Although many efforts have been made to create databases that store this information in computer readable form, populating these sources largely requires a manual process of interpreting and extracting interaction relationships from the biological research literature. Being able to efficiently and accurately automate the extraction of interactions from unstructured text, would greatly improve the content of these databases and provide a method for managing the continued growth of new literature being published. RESULTS: In this paper, we describe a system for extracting PGSM interactions from unstructured text. By utilizing a lexical analyzer and context free grammar (CFG), we demonstrate that efficient parsers can be constructed for extracting these relationships from natural language with high rates of recall and precision. Our results show that this technique achieved a recall rate of 83.5% and a precision rate of 93.1% for recognizing PGSM names and a recall rate of 63.9% and a precision rate of 70.2% for extracting interactions between these entities. In contrast to other published techniques, the use of a CFG significantly reduces the complexities of natural language processing by focusing on domain specific structure as opposed to analyzing the semantics of a given language. Additionally, our approach provides a level of abstraction for adding new rules for extracting other types of biological relationships beyond PGSM relationships. AVAILABILITY: The program and corpus are available by request from the authors. (+info)A medical dictionary is a reference book that contains definitions and explanations of medical terms and jargon. It serves as a useful tool for healthcare professionals, students, patients, and anyone else who needs to understand medical terminology. Medical dictionaries can include definitions of diseases, conditions, treatments, procedures, drugs, equipment, anatomy, and more. They may also provide pronunciation guides, etymologies, and abbreviations.
Medical dictionaries can be found in print or digital form, and some are specialized to cover specific areas of medicine, such as oncology, psychiatry, or surgery. Some medical dictionaries are also bilingual, providing translations of medical terms between different languages. Overall, a medical dictionary is an essential resource for anyone who needs to communicate effectively in the field of medicine.
"Dictionaries as Topic" is a medical subject heading (MeSH) that refers to the study or discussion of dictionaries as a reference source in the field of medicine. Dictionaries used in this context are specialized works that provide definitions and explanations of medical terms, concepts, and technologies. They serve as important tools for healthcare professionals, researchers, students, and patients to communicate effectively and accurately about health and disease.
Medical dictionaries can cover a wide range of topics, including anatomy, physiology, pharmacology, pathology, diagnostic procedures, treatment methods, and medical ethics. They may also provide information on medical eponyms, abbreviations, symbols, and units of measurement. Some medical dictionaries are general in scope, while others focus on specific areas of medicine or healthcare, such as nursing, dentistry, veterinary medicine, or alternative medicine.
The use of medical dictionaries can help to ensure that medical terminology is used consistently and correctly, which is essential for accurate diagnosis, treatment planning, and communication among healthcare providers and between providers and patients. Medical dictionaries can also be useful for non-medical professionals who need to understand medical terms in the context of their work, such as lawyers, journalists, and policymakers.
A chemical dictionary is a reference book that provides definitions and explanations of various terms related to chemistry. It can include definitions for chemical elements, compounds, reactions, processes, theories, and techniques used in the field of chemistry. These dictionaries may also provide information on the historical development of chemical concepts and may include illustrations or diagrams to help clarify complex ideas. They are useful resources for students, researchers, and professionals in the field of chemistry, as well as for those who are interested in learning more about chemistry.
I believe there might be a bit of confusion in your question. A "dictionary" is not a medical term, but rather a general reference book or electronic resource that contains words, their meanings, pronunciations, and often additional information such as etymologies, usage examples, and related terms. It is used in various fields, including language learning, writing, reading, and research.
However, if you are looking for the medical definition of 'dictionary' as a term within the field of medical informatics or health terminologies, it generally refers to a controlled vocabulary or standardized list of terms that are used to describe and code specific concepts within the medical field. These dictionaries help ensure consistency and accuracy in the documentation, communication, and analysis of healthcare information. Examples include the International Classification of Diseases (ICD), Systematized Nomenclature of Medicine--Clinical Terms (SNOMED CT), and Logical Observation Identifiers Names and Codes (LOINC).
I believe you are asking for a medical definition of "pharmacodictionary" or "drug dictionary." A pharmacodictionary, also known as a drug dictionary or formulary, is a comprehensive and authoritative listing of information about medications, including their generic and brand names, ingredients, uses, dosages, side effects, contraindications, and interactions with other drugs.
Pharmacodictionaries are used by healthcare professionals, such as doctors, nurses, and pharmacists, to help them make informed decisions when prescribing or administering medications to patients. They may also be used by patients and caregivers to better understand their medications and ensure safe and effective use. Pharmacodictionaries can be found in various formats, including print, online databases, and mobile applications.
"Terminology as a topic" in the context of medical education and practice refers to the study and use of specialized language and terms within the field of medicine. This includes understanding the meaning, origins, and appropriate usage of medical terminology in order to effectively communicate among healthcare professionals and with patients. It may also involve studying the evolution and cultural significance of medical terminology. The importance of "terminology as a topic" lies in promoting clear and accurate communication, which is essential for providing safe and effective patient care.
I'm not aware of a medical definition specifically for "Dictionaries, Dental." However, I can provide some information about dental dictionaries in general.
A dental dictionary is a reference book that contains definitions and explanations of terms related to dentistry, oral health, and related medical fields. These dictionaries are used by dental professionals, students, and researchers to understand and communicate effectively about various dental concepts, procedures, treatments, and conditions. They may include definitions for anatomical structures, dental materials, diagnostic tests, treatment options, and more.
Some popular dental dictionaries include:
1. Stedman's Medical Dictionary - includes a comprehensive list of medical terms with some dental-related entries.
2. The American Heritage Medical Dictionary - contains definitions for medical and dental terminology.
3. Dorland's Illustrated Medical Dictionary - another widely used reference book that includes dental terms.
4. Miller's Anesthesia, 8th Edition - while primarily focused on anesthesia, this resource also contains a substantial dental dictionary.
5. ADA Practical Guide to Patients' Rights and Responsibilities - published by the American Dental Association, this guide includes definitions related to patient rights and responsibilities in dental care.
These resources can be helpful for anyone looking to understand dental terminology or expand their knowledge of the field.
A polyglot dictionary is a type of reference book that contains translations of words and phrases between three or more languages. These dictionaries are designed to assist users in understanding and translating written or spoken text among multiple languages. They can be particularly useful for individuals who speak more than one language and need to translate or understand texts in multiple languages.
Polyglot dictionaries may include a variety of features, such as pronunciation guides, example sentences, and notes on grammar and usage. Some polyglot dictionaries may focus on specific subject areas, such as medical or technical terminology, while others may cover a broader range of vocabulary.
It is worth noting that while polyglot dictionaries can be helpful tools for language learners and translators, they are not a substitute for fluency in multiple languages. It is still important to have a strong understanding of the grammar, syntax, and cultural context of each language in order to effectively communicate and translate between them.
"Classical dictionaries" in a medical context typically refer to authoritative reference books that contain definitions and explanations of terms related to classical antiquity, particularly those from ancient Greece and Rome. These dictionaries may include definitions of medical terminology that has its roots in classical languages, such as Latin and Greek. They may also provide historical and cultural context for these terms, which can be useful for understanding their original meanings and uses.
Some examples of classical dictionaries that may be relevant to the study of medicine include:
* The Oxford Latin Dictionary
* A Latin Dictionary by Charlton T. Lewis and Charles Short
* A Greek-English Lexicon by Henry George Liddell and Robert Scott
* The Greek-English Lexicon by James H. Vince
These resources can be helpful for medical professionals, students, and researchers who are seeking to understand the origins and meanings of medical terminology that is based in classical languages.
'Abbreviations as Topic' in medical terms refers to the use and interpretation of abbreviated words or phrases that are commonly used in the field of medicine. These abbreviations can represent various concepts, such as medical conditions, treatments, procedures, diagnostic tests, and more.
Medical abbreviations are often used in clinical documentation, including patient records, progress notes, orders, and medication administration records. They help healthcare professionals communicate efficiently and effectively, reducing the need for lengthy descriptions and improving clarity in written communication.
However, medical abbreviations can also be a source of confusion and error if they are misinterpreted or used incorrectly. Therefore, it is essential to use standardized abbreviations that are widely recognized and accepted within the medical community. Additionally, healthcare professionals should always ensure that their use of abbreviations does not compromise patient safety or lead to misunderstandings in patient care.
Examples of commonly used medical abbreviations include:
* PT: Physical Therapy
* BP: Blood Pressure
* HR: Heart Rate
* Rx: Prescription
* NPO: Nothing by Mouth
* IV: Intravenous
* IM: Intramuscular
* COPD: Chronic Obstructive Pulmonary Disease
* MI: Myocardial Infarction (Heart Attack)
* Dx: Diagnosis
It is important to note that some medical abbreviations can have multiple meanings, and their interpretation may depend on the context in which they are used. Therefore, it is essential to use caution when interpreting medical abbreviations and seek clarification if necessary to ensure accurate communication and patient care.
I'm sorry for any confusion, but "Natural Language Processing" (NLP) is actually a subfield of artificial intelligence that focuses on the interaction between computers and human language. It involves developing algorithms and software to understand, interpret, and generate human language in a valuable way.
In a medical context, NLP can be used to analyze electronic health records, clinical notes, and other forms of medical documentation to extract meaningful information, support clinical decision-making, and improve patient care. For example, NLP can help identify patients at risk for certain conditions, monitor treatment responses, and detect adverse drug events.
However, NLP is not a medical term or concept itself, so it doesn't have a specific medical definition.
Abstracting and indexing are processes used in the field of information science to organize, summarize, and categorize published literature, making it easier for researchers and other interested individuals to find and access relevant information.
Abstracting involves creating a brief summary of a publication, typically no longer than a few hundred words, that captures its key points and findings. This summary is known as an abstract and provides readers with a quick overview of the publication's content, allowing them to determine whether it is worth reading in full.
Indexing, on the other hand, involves categorizing publications according to their subject matter, using a controlled vocabulary or set of keywords. This makes it easier for users to search for and find publications on specific topics, as they can simply look up the relevant keyword or subject heading in the index.
Together, abstracting and indexing are essential tools for managing the vast and growing amount of published literature in any given field. They help ensure that important research findings and other information are easily discoverable and accessible to those who need them, thereby facilitating the dissemination of knowledge and advancing scientific progress.
The Unified Medical Language System (UMLS) is a set of files and software developed by the U.S. National Library of Medicine (NLM). It provides a comprehensive source of biomedical and health-related terms aimed at unifying and standardizing the language used in various areas of the medical field, such as clinical care, research, and education.
The UMLS includes many different vocabularies, classifications, and coding systems, including but not limited to:
* Systematized Nomenclature of Medicine--Clinical Terms (SNOMED CT)
* International Classification of Diseases (ICD)
* Current Procedural Terminology (CPT)
* Logical Observation Identifiers Names and Codes (LOINC)
By integrating these various terminologies, the UMLS enables more effective searching, information retrieval, and data analysis across different systems and databases. It also supports natural language processing (NLP) applications, such as text mining and clinical decision support systems.
I'm sorry for any confusion, but "names" is not a medical term that can be defined in a biological or clinical context. If you have any questions about medical terminology or concepts, I would be happy to try and help! Please provide more information or clarify your question.
'Information Storage and Retrieval' in the context of medical informatics refers to the processes and systems used for the recording, storing, organizing, protecting, and retrieving electronic health information (e.g., patient records, clinical data, medical images) for various purposes such as diagnosis, treatment planning, research, and education. This may involve the use of electronic health record (EHR) systems, databases, data warehouses, and other digital technologies that enable healthcare providers to access and share accurate, up-to-date, and relevant information about a patient's health status, medical history, and care plan. The goal is to improve the quality, safety, efficiency, and coordination of healthcare delivery by providing timely and evidence-based information to support clinical decision-making and patient engagement.
An encyclopedia is a comprehensive reference work containing articles on various topics, usually arranged in alphabetical order. In the context of medicine, a medical encyclopedia is a collection of articles that provide information about a wide range of medical topics, including diseases and conditions, treatments, tests, procedures, and anatomy and physiology. Medical encyclopedias may be published in print or electronic formats and are often used as a starting point for researching medical topics. They can provide reliable and accurate information on medical subjects, making them useful resources for healthcare professionals, students, and patients alike. Some well-known examples of medical encyclopedias include the Merck Manual and the Stedman's Medical Dictionary.
Artificial Intelligence (AI) in the medical context refers to the simulation of human intelligence processes by machines, particularly computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction.
In healthcare, AI is increasingly being used to analyze large amounts of data, identify patterns, make decisions, and perform tasks that would normally require human intelligence. This can include tasks such as diagnosing diseases, recommending treatments, personalizing patient care, and improving clinical workflows.
Examples of AI in medicine include machine learning algorithms that analyze medical images to detect signs of disease, natural language processing tools that extract relevant information from electronic health records, and robot-assisted surgery systems that enable more precise and minimally invasive procedures.
"Subject Headings" is not a medical term per se, but rather a term used in the field of library science and information management. Subject headings are standardized terms or phrases used to describe the subject or content of a document, such as a book, article, or research paper, in a consistent and controlled way. They help organize and retrieve information by providing a uniform vocabulary for indexing and searching.
In the medical field, subject headings may be used in databases like PubMed, Medline, and CINAHL to categorize and search for medical literature. For example, the National Library of Medicine's MeSH (Medical Subject Headings) is a controlled vocabulary used for indexing and searching biomedical literature. It includes headings for various medical concepts, such as diseases, treatments, anatomical structures, and procedures, which can be used to search for relevant articles in PubMed and other databases.
An algorithm is not a medical term, but rather a concept from computer science and mathematics. In the context of medicine, algorithms are often used to describe step-by-step procedures for diagnosing or managing medical conditions. These procedures typically involve a series of rules or decision points that help healthcare professionals make informed decisions about patient care.
For example, an algorithm for diagnosing a particular type of heart disease might involve taking a patient's medical history, performing a physical exam, ordering certain diagnostic tests, and interpreting the results in a specific way. By following this algorithm, healthcare professionals can ensure that they are using a consistent and evidence-based approach to making a diagnosis.
Algorithms can also be used to guide treatment decisions. For instance, an algorithm for managing diabetes might involve setting target blood sugar levels, recommending certain medications or lifestyle changes based on the patient's individual needs, and monitoring the patient's response to treatment over time.
Overall, algorithms are valuable tools in medicine because they help standardize clinical decision-making and ensure that patients receive high-quality care based on the latest scientific evidence.
Medline is not a medical condition or term, but rather a biomedical bibliographic database, which is a component of the U.S. National Library of Medicine (NLM)'s PubMed system. It contains citations and abstracts from scientific literature in the fields of life sciences, biomedicine, and clinical medicine, with a focus on articles published in peer-reviewed journals. Medline covers a wide range of topics, including research articles, reviews, clinical trials, and case reports. The database is updated daily and provides access to over 26 million references from the years 1946 to the present. It's an essential resource for healthcare professionals, researchers, and students in the biomedical field.
Automated Pattern Recognition in a medical context refers to the use of computer algorithms and artificial intelligence techniques to identify, classify, and analyze specific patterns or trends in medical data. This can include recognizing visual patterns in medical images, such as X-rays or MRIs, or identifying patterns in large datasets of physiological measurements or electronic health records.
The goal of automated pattern recognition is to assist healthcare professionals in making more accurate diagnoses, monitoring disease progression, and developing personalized treatment plans. By automating the process of pattern recognition, it can help reduce human error, increase efficiency, and improve patient outcomes.
Examples of automated pattern recognition in medicine include using machine learning algorithms to identify early signs of diabetic retinopathy in eye scans or detecting abnormal heart rhythms in electrocardiograms (ECGs). These techniques can also be used to predict patient risk based on patterns in their medical history, such as identifying patients who are at high risk for readmission to the hospital.
Data mining, in the context of health informatics and medical research, refers to the process of discovering patterns, correlations, and insights within large sets of patient or clinical data. It involves the use of advanced analytical techniques such as machine learning algorithms, statistical models, and artificial intelligence to identify and extract useful information from complex datasets.
The goal of data mining in healthcare is to support evidence-based decision making, improve patient outcomes, and optimize resource utilization. Applications of data mining in healthcare include predicting disease outbreaks, identifying high-risk patients, personalizing treatment plans, improving clinical workflows, and detecting fraud and abuse in healthcare systems.
Data mining can be performed on various types of healthcare data, including electronic health records (EHRs), medical claims databases, genomic data, imaging data, and sensor data from wearable devices. However, it is important to ensure that data mining techniques are used ethically and responsibly, with appropriate safeguards in place to protect patient privacy and confidentiality.
I am not aware of a widely accepted medical definition for the term "software," as it is more commonly used in the context of computer science and technology. Software refers to programs, data, and instructions that are used by computers to perform various tasks. It does not have direct relevance to medical fields such as anatomy, physiology, or clinical practice. If you have any questions related to medicine or healthcare, I would be happy to try to help with those instead!
I'm afraid there seems to be a misunderstanding. Programming languages are a field of study in computer science and are not related to medicine. They are used to create computer programs, through the composition of symbols and words. Some popular programming languages include Python, Java, C++, and JavaScript. If you have any questions about programming or computer science, I'd be happy to try and help answer them!
I'm sorry for any confusion, but "semantics" is not a term that has a specific medical definition. Semantics is actually a branch of linguistics that deals with the study of meaning, reference, and the interpretation of signs and symbols, either individually or in combination. It is used in various fields including computer science, anthropology, psychology, and philosophy.
However, if you have any medical terms or concepts that you would like me to explain, I'd be happy to help!
A Database Management System (DBMS) is a software application that enables users to define, create, maintain, and manipulate databases. It provides a structured way to organize, store, retrieve, and manage data in a digital format. The DBMS serves as an interface between the database and the applications or users that access it, allowing for standardized interactions and data access methods. Common functions of a DBMS include data definition, data manipulation, data security, data recovery, and concurrent data access control. Examples of DBMS include MySQL, Oracle, Microsoft SQL Server, and MongoDB.
Automatic Data Processing (ADP) is not a medical term, but a general business term that refers to the use of computers and software to automate and streamline administrative tasks and processes. In a medical context, ADP may be used in healthcare settings to manage electronic health records (EHRs), billing and coding, insurance claims processing, and other data-intensive tasks.
The goal of using ADP in healthcare is to improve efficiency, accuracy, and timeliness of administrative processes, while reducing costs and errors associated with manual data entry and management. By automating these tasks, healthcare providers can focus more on patient care and less on paperwork, ultimately improving the quality of care delivered to patients.
I'm sorry for any confusion, but "physics" is not a term that has a medical definition. Physics is a branch of science that deals with the study of matter, energy, and their interactions. It may be studied in the context of medical physics, which involves the application of physical principles to medicine, such as in the use of radiation therapy for cancer treatment or imaging techniques like MRI and CT scans. However, "physics" itself is not a medical term with a specific definition within the field of medicine.
I'm sorry for any confusion, but "Systems Integration" is not a medical term per se. It is a term more commonly used in the fields of engineering, computer science, and information technology. However, I can provide you with a general definition:
Systems Integration refers to the process of combining different sub-systems or components into a single, cohesive system to allow seamless communication and data exchange between them. This integration aims to improve efficiency, performance, and overall functionality by unifying various standalone systems into an interconnected network that behaves as a unified whole.
In the context of healthcare, systems integration can be applied to merge different electronic health record (EHR) systems, medical devices, or other healthcare technologies to create a comprehensive, interoperable healthcare information system. This facilitates better care coordination, data sharing, and decision-making among healthcare providers, ultimately enhancing patient outcomes and satisfaction.
A database, in the context of medical informatics, is a structured set of data organized in a way that allows for efficient storage, retrieval, and analysis. Databases are used extensively in healthcare to store and manage various types of information, including patient records, clinical trials data, research findings, and genetic data.
As a topic, "Databases" in medicine can refer to the design, implementation, management, and use of these databases. It may also encompass issues related to data security, privacy, and interoperability between different healthcare systems and databases. Additionally, it can involve the development and application of database technologies for specific medical purposes, such as clinical decision support, outcomes research, and personalized medicine.
Overall, databases play a critical role in modern healthcare by enabling evidence-based practice, improving patient care, advancing medical research, and informing health policy decisions.
Data compression, in the context of medical informatics, refers to the process of encoding data to reduce its size while maintaining its integrity and accuracy. This technique is commonly used in transmitting and storing large datasets, such as medical images or genetic sequences, where smaller file sizes can significantly improve efficiency and speed up processing times.
There are two main types of data compression: lossless and lossy. Lossless compression ensures that the original data can be reconstructed exactly from the compressed data, making it essential for applications where data accuracy is critical, such as medical imaging or electronic health records. On the other hand, lossy compression involves discarding some redundant or less important data to achieve higher compression rates, but at the cost of reduced data quality.
In summary, data compression in a medical context refers to the process of reducing the size of digital data while maintaining its accuracy and integrity, which can improve efficiency in data transmission and storage.
Computational biology is a branch of biology that uses mathematical and computational methods to study biological data, models, and processes. It involves the development and application of algorithms, statistical models, and computational approaches to analyze and interpret large-scale molecular and phenotypic data from genomics, transcriptomics, proteomics, metabolomics, and other high-throughput technologies. The goal is to gain insights into biological systems and processes, develop predictive models, and inform experimental design and hypothesis testing in the life sciences. Computational biology encompasses a wide range of disciplines, including bioinformatics, systems biology, computational genomics, network biology, and mathematical modeling of biological systems.
A "periodical" in the context of medicine typically refers to a type of publication that is issued regularly, such as on a monthly or quarterly basis. These publications include peer-reviewed journals, magazines, and newsletters that focus on medical research, education, and practice. They may contain original research articles, review articles, case reports, editorials, letters to the editor, and other types of content related to medical science and clinical practice.
As a "Topic," periodicals in medicine encompass various aspects such as their role in disseminating new knowledge, their impact on clinical decision-making, their quality control measures, and their ethical considerations. Medical periodicals serve as a crucial resource for healthcare professionals, researchers, students, and other stakeholders to stay updated on the latest developments in their field and to share their findings with others.
RxNorm is a standardized nomenclature for clinical drugs produced by the US National Library of Medicine (NLM). It provides normalized names for medications, links its names to different drug delivery forms, and includes measures of the strengths of the drugs. RxNorm aims to represent the complex relationships between various medicinal products, including their ingredients, brand names, and generic counterparts. By providing a standardized vocabulary for clinical drugs, RxNorm facilitates safer medication prescribing, dispensing, and administration, as well as supports data analysis, research, and public health reporting.
I'm sorry for any confusion, but "multilingualism" is not a medical term. It refers to the ability to communicate in and use two or more languages. Multilingualism can be observed at various levels, such as speaking, reading, and writing, and it can be an innate ability or acquired through education and experience.
Multilingualism is a common phenomenon worldwide, and it has been shown to have cognitive benefits, such as improved problem-solving skills and increased cultural sensitivity. However, it is not a medical concept and does not fall under the purview of medical definitions.
PubMed is not a medical condition or term, but rather a biomedical literature search engine and database maintained by the National Center for Biotechnology Information (NCBI), a division of the U.S. National Library of Medicine (NLM). It provides access to life sciences literature, including journal articles in medicine, nursing, dentistry, veterinary medicine, health care systems, and preclinical sciences.
PubMed contains more than 30 million citations and abstracts from MEDLINE, life science journals, and online books. Many of the citations include links to full-text articles on publishers' websites or through NCBI's DocSumo service. Researchers, healthcare professionals, students, and the general public use PubMed to find relevant and reliable information in the biomedical literature for research, education, and patient care purposes.
A protein database is a type of biological database that contains information about proteins and their structures, functions, sequences, and interactions with other molecules. These databases can include experimentally determined data, such as protein sequences derived from DNA sequencing or mass spectrometry, as well as predicted data based on computational methods.
Some examples of protein databases include:
1. UniProtKB: a comprehensive protein database that provides information about protein sequences, functions, and structures, as well as literature references and links to other resources.
2. PDB (Protein Data Bank): a database of three-dimensional protein structures determined by experimental methods such as X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy.
3. BLAST (Basic Local Alignment Search Tool): a web-based tool that allows users to compare a query protein sequence against a protein database to identify similar sequences and potential functional relationships.
4. InterPro: a database of protein families, domains, and functional sites that provides information about protein function based on sequence analysis and other data.
5. STRING (Search Tool for the Retrieval of Interacting Genes/Proteins): a database of known and predicted protein-protein interactions, including physical and functional associations.
Protein databases are essential tools in proteomics research, enabling researchers to study protein function, evolution, and interaction networks on a large scale.
A factual database in the medical context is a collection of organized and structured data that contains verified and accurate information related to medicine, healthcare, or health sciences. These databases serve as reliable resources for various stakeholders, including healthcare professionals, researchers, students, and patients, to access evidence-based information for making informed decisions and enhancing knowledge.
Examples of factual medical databases include:
1. PubMed: A comprehensive database of biomedical literature maintained by the US National Library of Medicine (NLM). It contains citations and abstracts from life sciences journals, books, and conference proceedings.
2. MEDLINE: A subset of PubMed, MEDLINE focuses on high-quality, peer-reviewed articles related to biomedicine and health. It is the primary component of the NLM's database and serves as a critical resource for healthcare professionals and researchers worldwide.
3. Cochrane Library: A collection of systematic reviews and meta-analyses focused on evidence-based medicine. The library aims to provide unbiased, high-quality information to support clinical decision-making and improve patient outcomes.
4. OVID: A platform that offers access to various medical and healthcare databases, including MEDLINE, Embase, and PsycINFO. It facilitates the search and retrieval of relevant literature for researchers, clinicians, and students.
5. ClinicalTrials.gov: A registry and results database of publicly and privately supported clinical studies conducted around the world. The platform aims to increase transparency and accessibility of clinical trial data for healthcare professionals, researchers, and patients.
6. UpToDate: An evidence-based, physician-authored clinical decision support resource that provides information on diagnosis, treatment, and prevention of medical conditions. It serves as a point-of-care tool for healthcare professionals to make informed decisions and improve patient care.
7. TRIP Database: A search engine designed to facilitate evidence-based medicine by providing quick access to high-quality resources, including systematic reviews, clinical guidelines, and practice recommendations.
8. National Guideline Clearinghouse (NGC): A database of evidence-based clinical practice guidelines and related documents developed through a rigorous review process. The NGC aims to provide clinicians, healthcare providers, and policymakers with reliable guidance for patient care.
9. DrugBank: A comprehensive, freely accessible online database containing detailed information about drugs, their mechanisms, interactions, and targets. It serves as a valuable resource for researchers, healthcare professionals, and students in the field of pharmacology and drug discovery.
10. Genetic Testing Registry (GTR): A database that provides centralized information about genetic tests, test developers, laboratories offering tests, and clinical validity and utility of genetic tests. It serves as a resource for healthcare professionals, researchers, and patients to make informed decisions regarding genetic testing.
The Systematized Nomenclature of Medicine (SNOMED) is a systematically organized collection of medical terms that are used to describe medical diagnoses, findings, procedures, and other health-related concepts. It is a standardized terminology that is widely adopted in the field of healthcare and clinical research to facilitate accurate and consistent exchange of health information among different healthcare providers, institutions, and electronic health records (EHRs) systems.
SNOMED is designed to capture detailed clinical data and support effective clinical decision-making by providing a common language for describing and sharing clinical information. It includes over 350,000 concepts that are organized into hierarchies based on their relationships to each other. The hierarchical structure of SNOMED allows users to navigate through the terminology and find the most specific concept that describes a particular clinical phenomenon.
SNOMED is maintained by the International Health Terminology Standards Development Organization (IHTSDO), which is responsible for updating and expanding the terminology to reflect changes in medical knowledge and practice. SNOMED is used in many countries around the world, including the United States, Canada, Australia, and several European countries.
A Computerized Medical Record System (CMRS) is a digital version of a patient's paper chart. It contains all of the patient's medical history from multiple providers and can be shared securely between healthcare professionals. A CMRS includes a range of data such as demographics, progress notes, problems, medications, vital signs, past medical history, immunizations, laboratory data, and radiology reports. The system facilitates the storage, retrieval, and exchange of this information in an efficient manner, and can also provide decision support, alerts, reminders, and tools for performing data analysis and creating reports. It is designed to improve the quality, safety, and efficiency of healthcare delivery by providing accurate, up-to-date, and comprehensive information about patients at the point of care.
I'm sorry for any confusion, but "Internet" is a term that pertains to the global network of interconnected computers and servers that enable the transmission and reception of data via the internet protocol (IP). It is not a medical term and does not have a specific medical definition. If you have any questions related to medicine or health, I'd be happy to try to help answer them for you!
A bibliographic database is a type of database that contains records of publications, such as books, articles, and conference proceedings. These records typically include bibliographic information, such as the title, author, publication date, and source of the publication. Some bibliographic databases also include abstracts or summaries of the publications, and many provide links to the full text of the publications if they are available online.
Bibliographic databases are used in a variety of fields, including academia, medicine, and industry, to locate relevant publications on a particular topic. They can be searched using keywords, author names, and other criteria. Some bibliographic databases are general, covering a wide range of topics, while others are specialized and focus on a specific subject area.
In the medical field, bibliographic databases such as MEDLINE and PubMed are widely used to search for articles related to biomedical research, clinical practice, and public health. These databases contain records of articles from thousands of biomedical journals and can be searched using keywords, MeSH (Medical Subject Headings) terms, and other criteria.
In the context of medicine, "translating" often refers to the process of turning basic scientific discoveries into clinical applications that can directly benefit patients. This is also known as "translational research." It involves taking findings from laboratory studies and experiments, and finding ways to use that knowledge in the development of new diagnostic tools, treatments, or medical practices.
The goal of translation is to bridge the gap between scientific discovery and clinical practice, making sure that new advances in medicine are both safe and effective for patients. This process can be complex and challenging, as it requires collaboration between researchers, clinicians, regulatory agencies, and industry partners. It also involves rigorous testing and evaluation to ensure that any new treatments or interventions are both safe and effective.
A User-Computer Interface (also known as Human-Computer Interaction) refers to the point at which a person (user) interacts with a computer system. This can include both hardware and software components, such as keyboards, mice, touchscreens, and graphical user interfaces (GUIs). The design of the user-computer interface is crucial in determining the usability and accessibility of a computer system for the user. A well-designed interface should be intuitive, efficient, and easy to use, minimizing the cognitive load on the user and allowing them to effectively accomplish their tasks.
Proteins are complex, large molecules that play critical roles in the body's functions. They are made up of amino acids, which are organic compounds that are the building blocks of proteins. Proteins are required for the structure, function, and regulation of the body's tissues and organs. They are essential for the growth, repair, and maintenance of body tissues, and they play a crucial role in many biological processes, including metabolism, immune response, and cellular signaling. Proteins can be classified into different types based on their structure and function, such as enzymes, hormones, antibodies, and structural proteins. They are found in various foods, especially animal-derived products like meat, dairy, and eggs, as well as plant-based sources like beans, nuts, and grains.
Medical Informatics, also known as Healthcare Informatics, is the scientific discipline that deals with the systematic processing and analysis of data, information, and knowledge in healthcare and biomedicine. It involves the development and application of theories, methods, and tools to create, acquire, store, retrieve, share, use, and reuse health-related data and knowledge for clinical, educational, research, and administrative purposes. Medical Informatics encompasses various areas such as bioinformatics, clinical informatics, consumer health informatics, public health informatics, and translational bioinformatics. It aims to improve healthcare delivery, patient outcomes, and biomedical research through the effective use of information technology and data management strategies.
I'm sorry for any confusion, but "Online Systems" is not a medical term. It generally refers to computer systems or networks that are connected to the internet and can be accessed remotely. In a medical context, it could refer to various online tools and platforms used in healthcare, such as electronic health records, telemedicine systems, or medical research databases. However, without more specific context, it's difficult to provide an accurate medical definition.
A disease is a condition that impairs normal functioning and causes harm to the body. It is typically characterized by a specific set of symptoms and may be caused by genetic, environmental, or infectious agents. A disease can also be described as a disorder of structure or function in an organism that produces specific signs or symptoms. Diseases can range from minor ones, like the common cold, to serious illnesses, such as heart disease or cancer. They can also be acute, with a sudden onset and short duration, or chronic, lasting for a long period of time. Ultimately, a disease is any deviation from normal homeostasis that causes harm to an organism.
A Hospital Information System (HIS) is a comprehensive, integrated set of software solutions that support the management and operation of a hospital or healthcare facility. It typically includes various modules such as:
1. Electronic Health Record (EHR): A digital version of a patient's paper chart that contains all of their medical history from one or multiple providers.
2. Computerized Physician Order Entry (CPOE): A system that allows physicians to enter, modify, review, and communicate orders for tests, medications, and other treatments electronically.
3. Pharmacy Information System: A system that manages the medication use process, including ordering, dispensing, administering, and monitoring of medications.
4. Laboratory Information System (LIS): A system that automates and manages the laboratory testing process, from order entry to result reporting.
5. Radiology Information System (RIS): A system that manages medical imaging data, including scheduling, image acquisition, storage, and retrieval.
6. Picture Archiving and Communication System (PACS): A system that stores, distributes, and displays medical images from various modalities such as X-ray, CT, MRI, etc.
7. Admission, Discharge, and Transfer (ADT) system: A system that manages patient registration, scheduling, and tracking of their progress through the hospital.
8. Financial Management System: A system that handles billing, coding, and reimbursement processes.
9. Materials Management System: A system that tracks inventory, supply chain, and logistics operations within a healthcare facility.
10. Nursing Documentation System: A system that supports the documentation of nursing care, including assessments, interventions, and outcomes.
These systems are designed to improve the efficiency, quality, and safety of patient care by facilitating communication, coordination, and data sharing among healthcare providers and departments.
In a medical context, documentation refers to the process of recording and maintaining written or electronic records of a patient's health status, medical history, treatment plans, medications, and other relevant information. The purpose of medical documentation is to provide clear and accurate communication among healthcare providers, to support clinical decision-making, to ensure continuity of care, to meet legal and regulatory requirements, and to facilitate research and quality improvement initiatives.
Medical documentation typically includes various types of records such as:
1. Patient's demographic information, including name, date of birth, gender, and contact details.
2. Medical history, including past illnesses, surgeries, allergies, and family medical history.
3. Physical examination findings, laboratory and diagnostic test results, and diagnoses.
4. Treatment plans, including medications, therapies, procedures, and follow-up care.
5. Progress notes, which document the patient's response to treatment and any changes in their condition over time.
6. Consultation notes, which record communication between healthcare providers regarding a patient's care.
7. Discharge summaries, which provide an overview of the patient's hospital stay, including diagnoses, treatments, and follow-up plans.
Medical documentation must be clear, concise, accurate, and timely, and it should adhere to legal and ethical standards. Healthcare providers are responsible for maintaining the confidentiality of patients' medical records and ensuring that they are accessible only to authorized personnel.
Statistical models are mathematical representations that describe the relationship between variables in a given dataset. They are used to analyze and interpret data in order to make predictions or test hypotheses about a population. In the context of medicine, statistical models can be used for various purposes such as:
1. Disease risk prediction: By analyzing demographic, clinical, and genetic data using statistical models, researchers can identify factors that contribute to an individual's risk of developing certain diseases. This information can then be used to develop personalized prevention strategies or early detection methods.
2. Clinical trial design and analysis: Statistical models are essential tools for designing and analyzing clinical trials. They help determine sample size, allocate participants to treatment groups, and assess the effectiveness and safety of interventions.
3. Epidemiological studies: Researchers use statistical models to investigate the distribution and determinants of health-related events in populations. This includes studying patterns of disease transmission, evaluating public health interventions, and estimating the burden of diseases.
4. Health services research: Statistical models are employed to analyze healthcare utilization, costs, and outcomes. This helps inform decisions about resource allocation, policy development, and quality improvement initiatives.
5. Biostatistics and bioinformatics: In these fields, statistical models are used to analyze large-scale molecular data (e.g., genomics, proteomics) to understand biological processes and identify potential therapeutic targets.
In summary, statistical models in medicine provide a framework for understanding complex relationships between variables and making informed decisions based on data-driven insights.
Shewanella is a genus of gram-negative, facultatively anaerobic bacteria that are widely distributed in various environments such as aquatic habitats, sediments, and occasionally in association with animals or humans. The bacteria are known for their ability to reduce a variety of substances, including metals, which can have implications in bioremediation and corrosion processes. Some species of Shewanella have been associated with human infections, typically occurring in individuals with underlying health conditions or compromised immune systems. However, these cases are relatively rare.
Adverse Drug Reaction (ADR) Reporting Systems are spontaneous reporting systems used for monitoring the safety of authorized medicines in clinical practice. These systems collect and manage reports of suspected adverse drug reactions from healthcare professionals, patients, and pharmaceutical companies. The primary objective of ADR reporting systems is to identify new risks or previously unrecognized risks associated with the use of a medication, monitor the frequency and severity of known adverse effects, and contribute to post-marketing surveillance and pharmacovigilance activities.
Healthcare professionals, including physicians, pharmacists, and nurses, are encouraged to voluntarily report any suspected adverse drug reactions they encounter during their practice. In some countries, patients can also directly report any suspected adverse reactions they experience after taking a medication. Pharmaceutical companies are obligated to submit reports of adverse events identified through their own pharmacovigilance activities or from post-marketing surveillance studies.
The data collected through ADR reporting systems are analyzed to identify signals, which are defined as new, changing, or unknown safety concerns related to a medicine or vaccine. Signals are further investigated and evaluated for causality and clinical significance. If a signal is confirmed, regulatory actions may be taken, such as updating the product label, issuing safety communications, or restricting the use of the medication.
Examples of ADR reporting systems include the US Food and Drug Administration's (FDA) Adverse Event Reporting System (FAERS), the European Medicines Agency's (EMA) EudraVigilance, and the World Health Organization's (WHO) Uppsala Monitoring Centre.
Pharmaceutical preparations refer to the various forms of medicines that are produced by pharmaceutical companies, which are intended for therapeutic or prophylactic use. These preparations consist of an active ingredient (the drug) combined with excipients (inactive ingredients) in a specific formulation and dosage form.
The active ingredient is the substance that has a therapeutic effect on the body, while the excipients are added to improve the stability, palatability, bioavailability, or administration of the drug. Examples of pharmaceutical preparations include tablets, capsules, solutions, suspensions, emulsions, ointments, creams, and injections.
The production of pharmaceutical preparations involves a series of steps that ensure the quality, safety, and efficacy of the final product. These steps include the selection and testing of raw materials, formulation development, manufacturing, packaging, labeling, and storage. Each step is governed by strict regulations and guidelines to ensure that the final product meets the required standards for use in medical practice.
I must clarify that there is no specific medical definition for "Software Design." Software design is a term used in the field of software engineering and development, which includes the creation of detailed plans, schemas, and models that describe how a software system or application should be constructed and implemented. This process involves various activities such as defining the architecture, components, modules, interfaces, data structures, and algorithms required to build the software system.
However, in the context of medical software or healthcare applications, software design would still refer to the planning and structuring of the software system but with a focus on addressing specific needs and challenges within the medical domain. This might include considerations for data privacy and security, regulatory compliance (such as HIPAA or GDPR), integration with existing health IT systems, user experience (UX) design for healthcare professionals and patients, and evidence-based decision support features.
A genetic database is a type of biomedical or health informatics database that stores and organizes genetic data, such as DNA sequences, gene maps, genotypes, haplotypes, and phenotype information. These databases can be used for various purposes, including research, clinical diagnosis, and personalized medicine.
There are different types of genetic databases, including:
1. Genomic databases: These databases store whole genome sequences, gene expression data, and other genomic information. Examples include the National Center for Biotechnology Information's (NCBI) GenBank, the European Nucleotide Archive (ENA), and the DNA Data Bank of Japan (DDBJ).
2. Gene databases: These databases contain information about specific genes, including their location, function, regulation, and evolution. Examples include the Online Mendelian Inheritance in Man (OMIM) database, the Universal Protein Resource (UniProt), and the Gene Ontology (GO) database.
3. Variant databases: These databases store information about genetic variants, such as single nucleotide polymorphisms (SNPs), insertions/deletions (INDELs), and copy number variations (CNVs). Examples include the Database of Single Nucleotide Polymorphisms (dbSNP), the Catalogue of Somatic Mutations in Cancer (COSMIC), and the International HapMap Project.
4. Clinical databases: These databases contain genetic and clinical information about patients, such as their genotype, phenotype, family history, and response to treatments. Examples include the ClinVar database, the Pharmacogenomics Knowledgebase (PharmGKB), and the Genetic Testing Registry (GTR).
5. Population databases: These databases store genetic information about different populations, including their ancestry, demographics, and genetic diversity. Examples include the 1000 Genomes Project, the Human Genome Diversity Project (HGDP), and the Allele Frequency Net Database (AFND).
Genetic databases can be publicly accessible or restricted to authorized users, depending on their purpose and content. They play a crucial role in advancing our understanding of genetics and genomics, as well as improving healthcare and personalized medicine.
Dictionary of American Slang
Miller-Keane Encyclopedia & Dictionary of Medicine, Nursing, and Allied Health
The Official Politically Correct Dictionary and Handbook
Gynaecology
Mexican art
List of practical joke topics
Euthanasia
Coprolite
Iphisa
Stereoisomerism
Cultural references to donkeys
Biographical dictionary
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Dead cotton
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Brazilian Carnival
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Santalum album
List of omics topics in biology
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Cider
United States Coast Guard Cutter
Johann Christoph Döderlein
Baptism in Mormonism
Ecosystems Topic Dictionary Wordlist
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Dictionaries - Zaccai
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YourDictionary: Definitions and Meanings From Over a Dozen Trusted Dictionary Sources
Which dictionary (book title or web url) do you use most?
Overview of the Subject of Buzi - Bible Dictionaries at a Glance
Activity Lists and Attributes vs WBS Dictionary - PM PrepCast Forum
Online Encyclopedia and Dictionary - 1993
Staff View: Biographical dictionary of Tibet and Tibetan Buddhism
Staff View: Tibetan-English Dictionary
dictionary<...
Cambridge Dictionary updates definition of 'woman'
Blair, Eric Arthur [pseud. George Orwell] (1903-1950), political writer and essayist | Oxford Dictionary of National Biography
Ali, Abdullah Yusuf (1872-1953), Indian civil servant and Islamic scholar | Oxford Dictionary of National Biography
von - Wiktionary, the free dictionary
Orthogonality-Promoting Dictionary Learning via Bayesian Inference - AAAI
Spawn Quotes - 2 quotes on Spawn Science Quotes - Dictionary of Science Quotations and Scientist Quotes
Evelyn Waugh Quotes - 5 Science Quotes - Dictionary of Science Quotations and Scientist Quotes
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3,000 Most Common Words in English | Britannica Dictionary
Birds (English-German) Picture Dictionary
Bible Dictionary1
- These files are public domain and are a derivative of the topics are from American Tract Society Bible Dictionary published in 1859. (studylight.org)
20211
- 2021). In Venes, D. (Ed.), Taber's Medical Dictionary (24th ed. (tabers.com)
English4.today Dictionary1
- Some words are not included in the English4.today Dictionary and these include common words such as 'and', 'it', 'if' and many of the prepositions. (english4today.com)
Definitions3
- I am a volunteer teacher of English to speakers of other languages, and for them I recommend the Longman Dictionary of Contemporary English because it is one of the first computer compiled dictionaries, the definitions all being constructed from a minimal vocabulary of English words. (answerbag.com)
- However, the Cambridge Dictionary is not the first dictionary to change its definitions . (telegraph.co.uk)
- Cambridge Dictionary was asked what prompted the updated definitions, and when exactly they were changed. (telegraph.co.uk)
Search2
- Send the topic 'Search dictionaries with a single click on your browser' to a friend. (translatum.gr)
- Articles by Country Search - Search articles by the topic country. (cdc.gov)
English27
- O xford English Dictionary - OED, the only one that's really worth anything. (answerbag.com)
- F or myself, The Shorter Oxford English Dictionary when I am in a hurry. (answerbag.com)
- The Compact Edition of the Oxford English Dictionary (which is a photographic reduction of the 20 odd volumes of the full-sized dictionary) is the best in the world, but one needs a magnifying glass to read the entries. (answerbag.com)
- Our dictionaries are written for learners of English and are designed to help users understand English as it is currently used. (telegraph.co.uk)
- We regularly update our dictionary to reflect changes in how English is used, based on analysis of data from this corpus. (telegraph.co.uk)
- The best thing about our English to Chinese dictionary and translator app is that it is free to use and that you can download it on your Android device. (softonic.com)
- The Chinese English Dictionary Pro is a free, user-friendly dictionary app that can be downloaded on your Android device. (softonic.com)
- Quictionary is a free, no-frills English-Chinese and Chinese-English online dictionary available on Android. (softonic.com)
- Offline Dictionary Lite ENGCH is a free English to Chinese dictionary designed for Android users. (softonic.com)
- Lantern Dict (Từ điển chữ Hán) is a free Chinese-English/Chinese-Vietnamese dictionary that is available for Android. (softonic.com)
- English Chinese Dictionary 辞典 is an Android app that provides a basic English Chinese dictionary. (softonic.com)
- VoiceTube Dictionary is an offline English-Chinese dictionary that offers pronunciation assistance and word form explanations. (softonic.com)
- English Chinese Dictionary is a simple, fast, and effective application for learning Chinese and English. (softonic.com)
- Lantern Dict - Từ điển chữ Hán is a free Chinese-English dictionary that offers a wide range of features to aid in language learning and reference. (softonic.com)
- Tongan-English Dictionary is a comprehensive language reference tool available for Android users. (softonic.com)
- This free offline dictionary app for Android is perfect for learning the Finnish language and English. (softonic.com)
- The English to Polish Dictionary - Free Translator is an innovative tool that can help you develop your language skills and learn a new vocabulary. (softonic.com)
- Swahili English Dictionary and Translator is an offline application that offers you a real dictionary. (softonic.com)
- English Amharic Dictionary is a full version offline dictionary available for Android devices. (softonic.com)
- A free Gujarati to English and English to Gujarati Dictionary is available for Android devices. (softonic.com)
- This is a free offline Hausa English Dictionary that lets you look up words from various sources: Internet Browser or Application sharing options. (softonic.com)
- English to Welsh Dictionary - Free Translator is an app that helps you translate from English to Welsh and vice versa. (softonic.com)
- English to Thai Dictionary - Free Translator is a free app available on Android devices that provides a comprehensive tool for learning a new language. (softonic.com)
- Our free dictionary app, called English Assamese Dictionary, is the best way to learn the Assamese language. (softonic.com)
- It is the best dictionary for Khmer language and English. (softonic.com)
- This means that we all need to use dictionaries and automatic spell-checks when we write in English. (lu.se)
- As defined by The American Heritage Dictionary of the English Language: 4th edition 1. (curlie.org)
Https1
- https://www.studylight.org/​dictionaries/​eng/​hdb/​b/blasphemy.html. (studylight.org)
Vocabulary Builder1
- The English4Today Online Dictionary and Vocabulary Builder can also be used to improve the skills of your students, children or employees. (english4today.com)
English4Today1
- With the English4Today Online Dictionary and set of vocabulary building tools you can quickly increase your vocabulary and improve your communication skills . (english4today.com)
20181
- OAKLAND, Calif. , Nov. 26, 2018 /PRNewswire/ -- Dictionary.com today announced it has named misinformation its 2018 Word of the Year. (prnewswire.com)
Environmental Health1
- It is not a complete dictionary of environmental health terms. (cdc.gov)
Quotations1
- As quoted in Tuttle Dictionary of Quotations (1989), 70. (todayinsci.com)
Android1
- Hanping Chinese Dictionary Pro is a free app for Android that belongs to the category Books & Reference, and has been developed by embermitre. (softonic.com)
Content1
- Every dictionaries are stored in their each subfolder in 'content' folder. (goldendict.org)
Definition4
- The Cambridge Dictionary has updated its definition of "woman" to include anyone who "identifies as female" regardless of their sex at birth. (telegraph.co.uk)
- The online dictionary recently added a supplementary definition of a "woman" that includes transgender people. (telegraph.co.uk)
- Responding to the Cambridge Dictionary definition updates, which were made in October, Dr Jane Hamlin, the president of the Beaumont Society, a charity which supports transgender and non-binary people, said: "This is such good news. (telegraph.co.uk)
- However, Maya Forstater, executive director of the campaign group, Sex Matters, said: "The primary dictionary definition remains adult human female and male. (telegraph.co.uk)
Words5
- People have always used words in different ways and the dictionary reflects that. (telegraph.co.uk)
- Look up words in the English4.Today Online Dictionary and add them to your own personal dictionary for vocabulary practice. (english4today.com)
- The dictionary will help you improve your language skills and learn a lot of new words. (softonic.com)
- The topics that the subsection on spelling is concerned with are commonly confused words, certain spelling rules/conventions, and some important differences between British and American spelling. (lu.se)
- Another subsection that has to to with the use of words is Dictionaries . (lu.se)
View1
- Taber's Online , www.tabers.com/tabersonline/view/Tabers-Dictionary/735193/all/OAE. (tabers.com)
Focuses1
- This section focuses on topics related to human or animal health, and medicine. (curlie.org)
Thesaurus1
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Page1
- W e have a Webster's Unabridged Dictionary always open to some page or another on its own special table. (answerbag.com)
Languages2
- How may I add additional languages to the dictionary? (libreoffice.org)
- The dictionary is a valuable reference resource for scholars of global hymnody, covering hymns from many countries and languages, historical and contemporary hymn writers, traditions from a wide range of denominations. (lu.se)
Apps1
- Developed by Bunna Apps, this dictionary offers translations. (softonic.com)
Biography1
- Dictionary of national biography. (archive.org)
General1
- Here you get some useful general information about dictionaries and how they could be used in academic writing. (lu.se)
Support2
- This resource contains a topic dictionary or wordlist to support writing about Ecosystems in three software formats: Kurzweil, CoWriter, and a text file. (setbc.org)
- Are there plans to add support for Android's Dictionary API for GoldenDict Pro? (goldendict.org)
Access1
- Users not affiliated with Lund University may be permitted access to Canterbury Dictionary of Hymnology, but only within the physical premises of Lund University Libraries. (lu.se)
Phrases1
- The following topics are dealt with here: Vocabulary Awareness, Useful Phrases and Expressions, Abbreviations, and Discipline Specific Vocabulary. (lu.se)
Data dictionary3
Download2
- Is there a good dictionary recommended by LO for download--good dictionary--the current one in Writer is sad (7.0). (libreoffice.org)
- If you want to learn Khmer, the first thing you need to do is to download this free dictionary. (softonic.com)
Tasks1
- Dictionary Learning (DL) plays a crucial role in numerous machine learning tasks. (aaai.org)
Terms1
- He critiqued it for inconsistencies on what constitutes slang, but compared it favorably to Eric Partridge's Smaller Slang Dictionary because of the latter's lack of offensive terms. (wikipedia.org)
Version1
- The online version of the Canterbury Dictionary of Hymnology includes more than 4,000 entries, written by hundreds of authors, from dozens of countries. (lu.se)