Biomedical subjects

James H Kaufman

Publications and source records attributed to James H Kaufman.

3 recordsLinked to original sources

PubMed2006

An extensible spatial and temporal epidemiological modelling system.

BACKGROUND: This paper describes the Spatiotemporal Epidemiological Modeller (STEM) which is an extensible software system and framework for modelling the spatial and temporal progression of multiple diseases affecting multiple populations in geographically distributed locations. STEM is an experiment in developing a software system that can model complex epidemiological scenarios while also being extensible by the research community. The ultimate goal of STEM is to provide a common modelling platform powerful enough to be sufficient for all modelling scenarios and extensible in a way that allows different researchers to combine their efforts in developing exceptionally good models. RESULTS: STEM is a powerful modelling system that allows researchers to model scenarios with unmixed populations that are not uniformly distributed and in which multiple populations exist that are being infected with multiple diseases. It's underlying representational framework, a graph, and its software architecture allow the system to be extended by incorporating software components developed by different researchers. CONCLUSION: This approach taken in the design of STEM creates a powerful platform for epidemiological research collaboration. Future versions of the system will make such collaborative efforts easy and common.

Animals↗

PubMed2006

Perceptual distance and the constancy of size and stereoscopic depth.

The relationship between distance and size perception is unclear because of conflicting results of tests investigating the size-distance invariance hypothesis (SDIH), according to which perceived size is proportional to perceived distance. We propose that response bias with regard to measures of perceived distance is at the root of the conflict. Rather than employ the usual method of magnitude estimation, the bias-free two-alternative forced choice (2AFC) method was used to determine the precision (1/sigma) of discriminating depth at different distances. The results led us to define perceptual distance as a bias free power function of physical distance, with an exponent of approximately 0.5. Similar measures involving size differences among stimuli of equal angular size yield the same power function of distance. In addition, size discrimination is noisier than depth discrimination, suggesting that distance information is processed prior to angular size. Size constancy implies that the perceived size is proportional to perceptual distance. Moreover, given a constant relative disparity, depth constancy implies that perceived depth is proportional to the square of perceptual distance. However, the function relating the uncertainties of depth and of size discrimination to distance is the same. Hence, depth and size constancy may be accounted for by the same underlying law.

Adult↗

PubMed2006

Lowering the barrier to a decentralized NHIN using the open healthcare framework.

In this paper, we discuss two important elements to lowering the barrier to creation of a National Health Information Network. The first element is the adoption of standards that will enable interoperability while guarantee open interfaces (and preventing vendor lock-in). The second element is the role of open source. While adoption of open standards by large EMR vendors is critically important to enterprise healthcare providers and payors, the availability of inexpensive (or free) standardized Healthcare Information Technology for small physician practices is critical. By analogy to the emergence of the World Wide Web, a framework for creating inexpensive and open source applications for physicians will be as important to realizing a National Health Information Network as availability of free browser technology was to the growth of the internet.

Ambulatory Care Information Systems↗