Prenatal diagnosis of congenital heart disease in the northern region of England: benefits of a training programme for obstetric ultrasonographers.
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OBJECTIVE: To examine the results of fetal cardiac scanning and audit the changes in performance resulting from the introduction of a training programme for obstetric ultrasonographers. METHODS: Using the database of the Northern Regional Congenital Abnormality Survey (NORCAS), fetuses with complex or significant congenital heart disease (CCHD) diagnosed prenatally in 1994 were identified. A simple programme of centralised and local training was instituted in 1995 by the department of paediatric cardiology to teach obstetric ultrasonographers in district general hospital maternity departments to identify congenital heart malformations. The results of the training programme were assessed by comparing the 1994 identification rate of CCHD with the rates for 1996 and 1997. RESULTS: Birth rate fell during the study from 35,026 in 1994 to 32,874 in 1997. Registration of CCHD also fell, from 115 in 1994 to 87 in 1997. Prenatal recognition of CCHD rose from 17% in 1994 to 30% in 1995 and 36% in 1996. In 1997 it fell slightly to 26.9%. The total number of scans did not change much year on year, but the number of parents choosing termination increased significantly (from 22.7% to 57%). CONCLUSIONS: A simple training programme for obstetric ultrasonographers increased their ability to detect serious congenital heart disease at a routine 18-20 week anomaly scan. With a termination rate of more than 50%, the incidence of CCHD in the population fell from 3.3/1000 to 2.6/1000 live births. This audit, conducted within a stable population using ascertainment by a well established fetal malformation registry, suggests that prenatal diagnosis may have a significant effect on the incidence of complex or serious congenital cardiac malformations. (+info)
CADMIUM II: acquisition and representation of radiological knowledge for computerized decision support in mammography.
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CADMIUM II is a system for the interpretation of mammograms. A novel aspect of the system is that it combines symbolic reasoning with image processing, in contrast with most other approaches, which use only image processing and rely on artificial neural networks (ANNs) to classify mammograms. A problem of ANNs is that the advice they give cannot be traced back to communicable diagnostic inferences. Our approach is to provide advice based on explicit knowledge about the diagnostic process. To this end, we have conducted a knowledge elicitation study which looked at the descriptors used by expert radiologists when making diagnostic decisions about mammograms. The analysis of the radiologists' reports yielded a set of salient diagnostic features. These were used to inform the advice provided by the symbolic decision making component of CADMIUM II. (+info)
NLP techniques associated with the OpenGALEN ontology for semi-automatic textual extraction of medical knowledge: abstracting and mapping equivalent linguistic and logical constructs.
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This research project presents methodological and theoretical issues related to the inter-relationship between linguistic and conceptual semantics, analysing the results obtained by the application of a NLP parser to a set of radiology reports. Our objective is to define a technique for associating linguistic methods with domain specific ontologies for semi-automatic extraction of intermediate representation (IR) information formats and medical ontological knowledge from clinical texts. We have applied the Edinburgh LTG natural language parser to 2810 clinical narratives describing radiology procedures. In a second step, we have used medical expertise and ontology formalism for identification of semantic structures and abstraction of IR schemas related to the processed texts. These IR schemas are an association of linguistic and conceptual knowledge, based on their semantic contents. This methodology aims to contribute to the elaboration of models relating linguistic and logical constructs based on empirical data analysis. Advance in this field might lead to the development of computational techniques for automatic enrichment of medical ontologies from real clinical environments, using descriptive knowledge implicit in large text corpora sources. (+info)
A broad-coverage natural language processing system.
(36/548)
Natural language processing systems (NLP) that extract clinical information from textual reports were shown to be effective for limited domains and for particular applications. Because an NLP system typically requires substantial resources to develop, it is beneficial if it is designed to be easily extendible to multiple domains and applications. This paper describes multiple extensions of an NLP system called MedLEE, which was originally developed for the domain of radiological reports of the chest, but has subsequently been extended to mammography, discharge summaries, all of radiology, electrocardiography, echocardiography, and pathology. (+info)
When seconds are counted: tools for mobile, high-resolution time-motion studies.
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Time-motion (TM) studies are often considered the gold-standard for measurements of the impact of computer systems on task flow and duration. However, in many clinical environments tasks occur too rapidly and have too short of a duration to be captured with conventional paper-based TM methods. Observers may also with to categorize caregiver activities along multiple axes simultaneously. This multi-axial characteristic of clinical activity has been modeled as multiple, parallel finite-state sets and implemented in three computerized data collection tools. Radiology reporting is a domain in which tasks can be characterized by multiple attributes. A radiologist may also switch among multiple tasks in a single minute. The use of these tools to measure the impact of an Automated Speech Recognition (ASR) system on Radiology reporting is presented. (+info)
Integrated Obstetric Curriculum for Obstetrics and Gynecology Residency, Radiology Residency and Maternal-Fetal Medicine Fellowship program at an accredited American Institute of Ultrasound in Medicine Diagnostic Ultrasound Center.
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OBJECTIVE: The purpose of this work was to demonstrate the approach to developing an integrated curriculum for obstetric ultrasound training by utilizing an accredited American Institute of Ultrasound in Medicine teaching platform. METHODS: During the 1996-98 academic years, the American College of Obstetricians and Gynecologists and American Institute of Ultrasound in Medicine guidelines for ultrasound performance and training were integrated into a multifaceted training program for obstetric and radiological residents and maternal-fetal medicine fellows consisting of a structured reading program, self study of a 35-mm slide program of normal/abnormal anatomy, a basic ultrasound and fetal echocardiography interactive CD program, hands-on supervised scanning program and practical and certificate-bearing fetal echocardiography courses for fellows. All obstetric residents were given pretests and post-tests to measure learning performance in the program. The results from these tests were analyzed for statistical significance. RESULTS: Thirteen obstetric residents completed the training program. The locally developed pretest showed a mean of 16/40 correct questions with an SD of 1.85. After completing the training, the mean obstetric resident scores on the post-test were 32/40 with an SD of 5.9. This difference was statistically significantly different, P < 0.009. Radiology residents showed an improvement from no residents passing the obstetric ultrasound portion on the 1996 Radiology Boards to 100% pass rate in 1997 (four residents per year) after completing the course. Maternal-fetal medicine fellows progressed from inability to perform acceptable fetal echocardiography to full ability to perform fetal echocardiographic examinations. CONCLUSION: An integrated approach to obstetric ultrasound training for obstetric and radiologic residents and maternal-fetal medicine fellows with multifaceted learning methods is easily achieved with available guidance from the American College of Obstetricians and Gynecologists and American Institute of Ultrasound in Medicine. (+info)
Computers in imaging and health care: now and in the future.
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Early picture archiving and communication systems (PACS) were characterized by the use of very expensive hardware devices, cumbersome display stations, duplication of database content, lack of interfaces to other clinical information systems, and immaturity in their understanding of the folder manager concepts and workflow reengineering. They were implemented historically at large academic medical centers by biomedical engineers and imaging informaticists. PACS were nonstandard, home-grown projects with mixed clinical acceptance. However, they clearly showed the great potential for PACS and filmless medical imaging. Filmless radiology is a reality today. The advent of efficient softcopy display of images provides a means for dealing with the ever-increasing number of studies and number of images per study. Computer power has increased, and archival storage cost has decreased to the extent that the economics of PACS is justifiable with respect to film. Network bandwidths have increased to allow large studies of many megabytes to arrive at display stations within seconds of examination completion. PACS vendors have recognized the need for efficient workflow and have built systems with intelligence in the management of patient data. Close integration with the hospital information system (HIS)-radiology information system (RIS) is critical for system functionality. Successful implementation of PACS requires integration or interoperation with hospital and radiology information systems. Besides the economic advantages, secure rapid access to all clinical information on patients, including imaging studies, anytime and anywhere, enhances the quality of patient care, although it is difficult to quantify. Medical image management systems are maturing, providing access outside of the radiology department to images and clinical information throughout the hospital or the enterprise via the Internet. Small and medium-sized community hospitals, private practices, and outpatient centers in rural areas will begin realizing the benefits of PACS already realized by the large tertiary care academic medical centers and research institutions. Hand-held devices and the Worldwide Web are going to change the way people communicate and do business. The impact on health care will be huge, including radiology. Computer-aided diagnosis, decision support tools, virtual imaging, and guidance systems will transform our practice as value-added applications utilizing the technologies pushed by PACS development efforts. Outcomes data and the electronic medical record (EMR) will drive our interactions with referring physicians and we expect the radiologist to become the informaticist, a new version of the medical management consultant. (+info)
Computer-assisted mammographic imaging.
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Computer-assisted mammography imaging comprises computer-based analysis of digitized images resulting in prompts aiding mammographic interpretation and computerized stereotactic localization devices which improve location accuracy. The commercial prompting systems available are designed to draw attention to mammographic abnormalities detected by algorithms based on symptomatic practise in North America. High sensitivity rates are important commercially but result in increased false prompt rates, which are known to distract radiologists. A national shortage of breast radiologists in the UK necessitates evaluation of such systems in a population breast screening programme to determine effectiveness in increasing cancer detection and feasibility of implementation. (+info)