284 research outputs found

    Information Retrieval from Hypertext: Update on the Dynamic Medical Handbook Project

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    This paper attempts to provide a perspective from which to develop a more complete theory of information retrieval from hypertext documents. Viewing hypertexts as large information spaces, we compare two general classes of navigation methods, classes we call local and global. We argue that global methods necessitate some form of “index space” conceptually separate from the hypertext “document space”. We note that the architectures of both spaces effect the ease with which one can apply various information retrieval algorithms. We identify a number of different index space and document space architectures and we discuss some of the associated trade-offs between hypertext functionality and computational complexity. We show how some index space architectures can be exploited for enhanced information retrieval, query refinement, and automated reasoning. Through analysis of a number of prototype systems, we discuss current limitations and future potentials for various hypertext information retrieval structures

    The Medical Informatics Group: Ongoing Research

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    Two current research projects within the Medical Informatics Group are described. The first, the Diabetes Data Management Project, has as its major goal the effective analysis, display, and summarization of information relevant to the care of insulin-dependent diabetics. These goals are achieved through the use of quantitative and qualitative modeling techniques, object-oriented graphical display methods, and natural language generation programs. The second research activity, the Hypertext Medical Handbook Project, emphasizes many aspects of electronic publishing and biomedical communication. In particular, the project explores machine-assisted information retrieval by combining user feedback with Bayesian inference networks

    A Psychophysical Comparison of Two Methods for Adaptive Histogram Equalization

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    Adaptive histogram equalization (ahe) is a method for adaptive contrast enhancement of digital images propped by Pizer et. Al.. It has the properties that it is an automatic, reproducible method for the simultaneous viewing of contrast within a digital image with a large dynamic range. Recent experiments have show that in specific cases, there is no significant difference in the ability of ahe and linear intensity windowing to display grey-scale contrast. More recently, Pizer et al. have proposed a variant of ahe which limits the allowed contrast enhancement of the image. The contrast-limited adaptive histogram equalization (clahe) produces images in which the noise content of an image is nor excessively enhanced, but in which sufficient contrast is provided for the visualization of structures within the image. Images processed with clahe have a more natural appearance and facilitate the comparison of different areas of an image. However, the reduced contrast enhancement of clahe may hinder the ability of an observer to detect the presence of some significant grey-scale contrast. In this work, a psychophysical observer experiment was performed to determine if there is a significant difference in the ability of ahe and clahe to depict grey-scale contrast. Observers were presented with CT images of the chest processed with ahe and clahe into some of which subtle artificial lesions were introduced. The observers were asked to rate their confidence regarding the presence of the lesions; this rating-scale data was analyzed using Receiver Operating Characteristic curving techniques. These ROC curves were compared for significant differences in the observers\u27 performances. In this study, no difference was found in the abilities of ahe and clahe to depict contrast information

    The Display and Manipulation of Temporal Information

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    Because medical data have complex temporal features, special techniques are required for storing, retrieving, and displaying clinical data from electronic databases. One significant problem caused by the temporal nature of medical data has been called the temporal granularity problem. The temporal granularity problem is said to occur when the set of facts relevant to a specific problem changes as the time scale changes. We argue that what is needed to deal with changes in the relevant time scale are temporal granularity heuristics. One heuristic that we have explored is that, for any level of problem abstraction, and for each type of data item in the record, there exists an optimal level of temporal abstraction. We describe an implemented database kernel and a graphical user interface that have features designed specially to support this temporal granularity heuristic. The basis for our solution is the use of temporal abstraction and temporal granularity. This heuristic encodes the relevant behavior of each type of event at different levels of temporal granularity. In doing so, we can define a specific behavior for each type of data as the level of abstraction changes

    Validity of self-reported history of Chlamydia trachomatis infection

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    BACKGROUND: Chlamydia trachomatis infection is common and largely asymptomatic in women. If untreated, it can lead to sequelae such as pelvic inflammatory disease and infertility. It is unknown whether a patient's self-reported history of Chlamydia trachomatis infection is a valid marker of past infection. OBJECTIVE: Our objective was to evaluate the validity of women's self-reported history of Chlamydia trachomatis infection compared with Chlamydia trachomatis serology, a marker for previous infection. STUDY DESIGN: We analyzed data from the Fertility After Contraception Termination study. We compared participants' survey responses with the question, "Have you ever been told by a health care provider that you had Chlamydia?" to serological test results indicating the presence or absence of antibodies to Chlamydia trachomatis as assessed by a microimmunofluorescence assay. Prevalence of past infection, sensitivity, specificity, predictive values, and likelihood ratios were calculated. The Cohen's kappa statistic was computed to assess agreement between self-report and serology. RESULTS: Among 409 participants, 108 (26%) reported having a history of Chlamydia trachomatis infection, whereas 146 (36%) had positive serological test results. Relative to positive microimmunofluorescence assay, the sensitivity and specificity of self-reported history of Chlamydia trachomatis infection were 52.1% (95% confidence interval, 43.6-60.4%) and 87.8% (95% confidence interval, 83.3-91.5%), respectively. The positive predictive value of the self-report was 70.4% (95% confidence interval, 60.8-78.8%), and the negative predictive value was 76.7% (95% confidence interval, 71.6-81.4%). The likelihood ratio was found to be 4.28. Agreement between self-report and serology was found to be moderate (kappa = 0.42, P < .001). CONCLUSION: Self-reported history of Chlamydia trachomatis infection commonly yields false-negative and false-positive results. When definitive status of past Chlamydia trachomatis infection is needed, serology should be obtained

    759–5 Use of an Interactive Electronic Whiteboard to Teach Clinical Cardiology Decision Analysis to Medical Students

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    We used innovative state-of-the-art computer and collaboration technologies to teach first-year medical students an analytic methodology to solve difficult clinical cardiology problems to make informed medical decisions. Clinical examples included the decision to administer thrombolytic therapy considering the risk of hemorrhagic stroke, and activity recommendations for athletes at risk for sudden death. Students received instruction on the decision-analytic approach which integrates pathophysiology, treatment efficacy, diagnostic test interpretation, health outcomes, patient preferences, and cost-effectiveness into a decision-analytic model.The traditional environment of a small group and blackboard was significantly enhanced by using an electronic whiteboard, the Xerox LiveBoard™. The LiveBoard features an 80486-based personal computer, large (3’×4’) display, and wireless pens for input. It allowed the integration of decision-analytic software, statistical software, digital slides, and additional media. We developed TIDAL (Team Interactive Decision Analysis in the Large-screen environment), a software package to interactively construct decision trees, calculate expected utilities, and perform one- and two-way sensitivity analyses using pen and gesture inputs. The Live Board also allowed the novel incorporation of Gambler, a utility assessment program obtained from the New England Medical Center. Gambler was used to obtain utilities for outcomes such as non-disabling hemorrhagic stroke. The interactive nature of the LiveBoard allowed real-time decision model development by the class, followed by instantaneous calculation of expected utilities and sensitivity analyses. The multimedia aspect and interactivity were conducive to extensive class participation.Ten out of eleven students wanted decision-analytic software available for use during their clinical years and all students would recommend the course to next year's students. We plan to experiment with the electronic collaboration features of this technology and allow groups separated by time or space to collaborate on decisions and explore the models created

    Joint estimation of gene conversion rates and mean conversion tract lengths from population SNP data

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    Motivation: Two known types of meiotic recombination are crossovers and gene conversions. Although they leave behind different footprints in the genome, it is a challenging task to tease apart their relative contributions to the observed genetic variation. In particular, for a given population SNP dataset, the joint estimation of the crossover rate, the gene conversion rate and the mean conversion tract length is widely viewed as a very difficult problem

    Implementation of an innovative, integrated electronic medical record (EMR) and public health information exchange for HIV/AIDS

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    Louisiana is severely affected by HIV/AIDS, ranking fifth in AIDS rates in the USA. The Louisiana Public Health Information Exchange (LaPHIE) is a novel, secure bi-directional public health information exchange, linking statewide public health surveillance data with electronic medical record data. LaPHIE alerts medical providers when individuals with HIV/AIDS who have not received HIV care for >12 months are seen at any ambulatory or inpatient facility in an integrated delivery network. Between 2/1/2009 and 1/31/2011, 488 alerts identified 345 HIV positive patients. Of those identified, 82% had at least one CD4 or HIV viral load test over the study follow-up period. LaPHIE is an innovative use of health information exchange based on surveillance data and real time clinical messaging, facilitating rapid provider notification of those in need of treatment. LaPHIE successfully reduces critical missed opportunities to intervene with individuals not in care, leveraging information historically collected solely for public health purposes, not health care delivery, to improve public health
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