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Biomedical subjects

M E Frisse

Publications and source records attributed to M E Frisse.

33 records · Page 2Linked to original sources
PubMed1994

Interactive electronic whiteboards in the medical classroom.

Most research on computer-assisted instruction has concentrated on developing systems to be used outside the teaching environment to supplement or complement in-class teaching. We believe that interactive large-screen computers can be used effectively in the classroom as electronic whiteboards to more effectively teach select medical school courses. We describe our experience with one such device, the Xerox LiveBoard, to teach a course on computer-assisted clinical decision analysis to a group of first-year medical students.

Computer-Assisted Instruction↗
PubMed1993

A tutorial introduction to stochastic simulation algorithms for belief networks.

Belief networks combine probabilistic knowledge with explicit information about conditional independence assumptions. A belief network consists of a directed acyclic graph in which the nodes represent variables and the edges express relationships of conditional dependence. When information about one variable's state is given to the network in the form of evidence, an update algorithm computes the posterior marginal probability distributions for the remaining variables in the network. Many algorithms for performing this inference task have been proposed. Exact algorithms report precise results for some classes of networks, but take exponential time (in the number of nodes) both in the worst case and for many interesting networks. Stochastic simulation algorithms estimate the posterior marginal probability distribution for many graph topologies that would require exponential time when using an exact algorithm. Nonetheless, for some belief networks, stochastic simulation algorithms are also known to have exponential worst case performance. This article describes at a tutorial level several stochastic simulation algorithms for belief networks, and illustrates them on some simple examples. In addition, the theoretical and empirical performance of the algorithms is briefly surveyed.

Algorithms↗
PubMed1993

Making networks work.

Explore the source record for details and available documents.

Academic Medical Centers↗
PubMed1992

Ubiquitous computing.

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Academic Medical Centers↗
PubMed1992

A method for publishing genomic maps.

We describe a method for the creation, manipulation and publication of physical human genome maps. Employing an "intelligent" document interface metaphor, our system uses a commercially available programmable document production system as an interface to primary genetic data resources and externally created mapping algorithms. Our document architecture distinguishes between primary data (usually obtained through database queries) and both manual and programmatic manipulations on these data. Our document architecture can be extended to accommodate a wide range of genetic and physical mapping problems. Because our approach is based on a widely available document preparation product, the principal focus of activity remains centered on the production of genomic maps that can be made available in a wide range of paper and electronic formats.

Algorithms↗
PubMed1991

Stochastic simulation algorithms for query networks.

One of the barriers to using belief networks for medical information retrieval is the computational cost of reasoning as the networks become large. Stochastic simulation algorithms allow one to compute approximations of probability values in a reasonable amount of time. We previously examined the performance of five stochastic simulation algorithms applied to four simple belief networks networks and found that the Self-Importance algorithm performed well. In this paper, we examine how the same five algorithms perform when applied to a belief network derived from the cardiovascular subtree of the Medical Subject Headings (MeSH). Both the Likelihood Weighting and Self-Importance algorithms perform well when applied to the MeSH-derived network, suggesting that stochastic simulation algorithms may provide reasonable performance in medical information retrieval settings.

Algorithms↗
PubMed1991

Information retrieval using a "digital book shelf".

WALT (Washington University's Approach to Lots of Text), is a prototype interface designed to support information retrieval research. The WALT interface serves as a "front end" to a wide array of retrieval engines including those based on Boolean retrieval, latent semantic indexing, term frequency--inverse document frequency, and Bayesian inference techniques. The WALT interface is composed of seven distinct components: a document examination component known as the Document Browsing Area; four navigation components called the Book Shelf, the Book Spine, the Table of Contents, and the Path Clipboard; a term-based information retrieval component called Control Panel; and a relevance feedback component known as the Reader Feedback Panel. WALT's most unique feature may be it's use of "book shelf" and "book spine" metaphors both to facilitate navigation and to provide a histogram-based display showing documents deemed appropriate for answering user queries.

Books↗
PubMed1989

A psychophysical comparison of two methods for adaptive histogram equalization.

Adaptive histogram equalization (AHE) is a method for adaptive contrast enhancement of digital images. It is an automatic, reproducible method for the simultaneous viewing of contrast within a digital image with a large dynamic range. Recent experiments have shown that in specific cases, there is no significant difference in the ability of AHE and linear intensity windowing to display gray-scale contrast. More recently, a variant of AHE which limits the allowed contrast enhancement of the image has been proposed. This contrast-limited adaptive histogram equalization (CLAHE) produces images in which the noise content of an image is not 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 gray-scale contrast. In this report, a psychophysical observer experiment was performed to determine if there is a significant difference in the ability of AHE and CLAHE to depict gray-scale contrast. Observers were presented with computed tomography (CT) images of the chest processed with AHE and CLAHE. Subtle artificial lesions were introduced into some images. The observers were asked to rate their confidence regarding the presence of the lesions; this rating-scale data was analyzed using receiver operating characteristic (ROC) curve techniques. These ROC curves were compared for significant differences in the observers' performances. In this report, no difference was found in the abilities of AHE and CLAHE to depict contrast information.

Contrast Media↗