A semantic lexicon for medical language processing.
OBJECTIVE: Construction of a resource that provides semantic information about words and phrases to facilitate the computer processing of medical narrative. DESIGN: Lexemes (words and word phrases) in the Specialist Lexicon were matched against strings in the 1997 Metathesaurus of the Unified Medical Language System (UMLS) developed by the National Library of Medicine. This yielded a "semantic lexicon," in which each lexeme is associated with one or more syntactic types, each of which can have one or more semantic types. The semantic lexicon was then used to assign semantic types to lexemes occurring in a corpus of discharge summaries (603,306 sentences). Lexical items with multiple semantic types were examined to determine whether some of the types could be eliminated, on the basis of usage in discharge summaries. A concordance program was used to find contrasting contexts for each lexeme that would reflect different semantic senses. Based on this evidence, semantic preference rules were developed to reduce the number of lexemes with multiple semantic types. RESULTS: Matching the Specialist Lexicon against the Metathesaurus produced a semantic lexicon with 75,711 lexical forms, 22,805 (30.1 percent) of which had two or more semantic types. Matching the Specialist Lexicon against one year's worth of discharge summaries identified 27,633 distinct lexical forms, 13,322 of which had at least one semantic type. This suggests that the Specialist Lexicon has about 79 percent coverage for syntactic information and 38 percent coverage for semantic information for discharge summaries. Of those lexemes in the corpus that had semantic types, 3,474 (12.6 percent) had two or more types. When semantic preference rules were applied to the semantic lexicon, the number of entries with multiple semantic types was reduced to 423 (1.5 percent). In the discharge summaries, occurrences of lexemes with multiple semantic types were reduced from 9.41 to 1.46 percent. CONCLUSION: Automatic methods can be used to construct a semantic lexicon from existing UMLS sources. This semantic information can aid natural language processing programs that analyze medical narrative, provided that lexemes with multiple semantic types are kept to a minimum. Semantic preference rules can be used to select semantic types that are appropriate to clinical reports. Further work is needed to increase the coverage of the semantic lexicon and to exploit contextual information when selecting semantic senses. (+info)
Virtual management of radiology examinations in the virtual radiology environment using common object request broker architecture services.
In the Department of Defense (DoD), US Army Medical Command is now embarking on an extremely exciting new project--creating a virtual radiology environment (VRE) for the management of radiology examinations. The business of radiology in the military is therefore being reengineered on several fronts by the VRE Project. In the VRE Project, a set of intelligent agent algorithms determine where examinations are to routed for reading bases on a knowledge base of the entire VRE. The set of algorithms, called the Meta-Manager, is hierarchical and uses object-based communications between medical treatment facilities (MTFs) and medical centers that have digital imaging network picture archiving and communications systems (DIN-PACS) networks. The communications is based on use of common object request broker architecture (CORBA) objects and services to send patient demographics and examination images from DIN-PACS networks in the MTFs to the DIN-PACS networks at the medical centers for diagnosis. The Meta-Manager is also responsible for updating the diagnosis at the originating MTF. CORBA services are used to perform secure message communications between DIN-PACS nodes in the VRE network. The Meta-Manager has a fail-safe architecture that allows the master Meta-Manager function to float to regional Meta-Manager sites in case of server failure. A prototype of the CORBA-based Meta-Manager is being developed by the University of Arizona's Computer Engineering Research Laboratory using the unified modeling language (UML) as a design tool. The prototype will implement the main functions described in the Meta-Manager design specification. The results of this project are expected to reengineer the process of radiology in the military and have extensions to commercial radiology environments. (+info)
Meta-manager: a requirements analysis.
The digital imaging network-picture-archiving and communications system (DIN-PACS) will be implemented in ten sites within the Great Plains Regional Medical Command (GPRMC). This network of PACS and teleradiology technology over a shared T1 network has opened the door for round the clock radiology coverage of all sites. However, the concept of a virtual radiology environment poses new issues for military medicine. A new workflow management system must be developed. This workflow management system will allow us to efficiently resolve these issues including quality of care, availability, severe capitation, and quality of the workforce. The design process of this management system must employ existing technology, operate over various telecommunication networks and protocols, be independent of platform operating systems, be flexible and scaleable, and involve the end user at the outset in the design process for which it is developed. Using the unified modeling language (UML), the specifications for this new business management system were created in concert between the University of Arizona and the GPRMC. These specifications detail a management system operating through a common object request brokered architecture (CORBA) environment. In this presentation, we characterize the Meta-Manager management system including aspects of intelligence, interfacility routing, fail-safe operations, and expected improvements in patient care and efficiency. (+info)
Detailed content and terminological properties of DSM-IV.
DSM-IV, the Diagnostic and Statistical Manual of Mental Disorders, is the internationally accepted standard for nomenclature and diagnosis in psychiatric practice. The objective of this project is to parse the rubric criteria of the DSM to extract the clinically detailed signs, symptoms, findings, and conditions that are present. These are a "latent terminology" implicit within the DSM, which is highly granular and clinically specific. This manuscript describes the content of these terms that heretofore existed sub rosa, though we recognize that during the authorship of the DSM such terms were constructed deliberately and systematically. Relevant characteristics of the classification system are briefly reviewed. Summary results of parsing the defining criteria for the 400 ICD-9 Codes enumerated in DSM-IV are presented. (+info)
Modeling the UMLS using an OODB.
The Unified Medical Language System combines many well established authoritative medical informatics terminologies in one system. Such a resource is very valuable to the healthcare industry. However, the UMLS is very large and complex and poses serious comprehension problems for users and maintenance personnel. Furthermore, the sets of concepts of semantic types are not semantically uniform and thus are difficult to study. We describe a method to represent two components of the UMLS, the Metathesaurus (META) and the Semantic Network, as an OODB. The resulting UMLS OODB schema is deeper and more refined than the Semantic Network. It offers semantically uniform classes, which improves support for comprehension and navigation of META. The UMLS OODB also exposes problems in the semantic type classifications. (+info)
Terminology issues in user access to Web-based medical information.
We conducted a study of user queries to the National Library of Medicine Web site over a three month period. Our purpose was to study the nature and scope of these queries in order to understand how to improve users' access to the information they are seeking on our site. The results show that the queries are primarily medical in content (94%), with only a small percentage (5.5%) relating to library services, and with a very small percentage (.5%) not being medically relevant at all. We characterize the data set, and conclude with a discussion of our plans to develop a UMLS-based terminology server to assist NLM Web users. (+info)
Mining molecular binding terminology from biomedical text.
Automatic access to information regarding macromolecular binding relationships would provide a valuable resource to the biomedical community. We report on a pilot project to mine such information from the molecular biology literature. The program being developed takes advantage of natural language processing techniques and is supported by two repositories of biomolecular knowledge. A formative evaluation has been conducted on a subset of MEDLINE abstracts. (+info)
MEDTAG: tag-like semantics for medical document indexing.
Medical documentation is central in health care, as it constitutes the main means of communication between care providers. However, there is a gap to bridge between storing information and extracting the relevant underlying knowledge. We believe natural language processing (NLP) is the best solution to handle such a large amount of textual information. In this paper we describe the construction of a semantic tagset for medical document indexing purposes. Rather than attempting to produce a home-made tagset, we decided to use, as far as possible, standard medicine resources. This step has led us to choose UMLS hierarchical classes as a basis for our tagset. We also show that semantic tagging is not only providing bases for disambiguisation between senses, but is also useful in the query expansion process of the retrieval system. We finally focus on assessing the results of the semantic tagger. (+info)