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By Eta S. Berner

It is a source ebook on clinical determination support systems for informatics experts, a textbook for lecturers or scholars in future health informatics and a complete creation for clinicians. It has turn into noticeable that, as well as physicians, different future health execs have desire of selection aid. consequently, the problems raised during this booklet practice to a huge diversity of clinicians. The booklet contains chapters written via across the world famous specialists at the layout, assessment and alertness of those platforms, who learn the effect of computer-based diagnostic instruments either from the practitioner’s viewpoint and that of the sufferer.

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Extra info for Clinical Decision Support Systems: Theory and Practice (Health Informatics)

Example text

By using numerical estimates of the probability of diseases, findings, and conditional probabilities, Bayes’ rule can help make medical decisions. One might imagine a simple CDSS in which one enters a single symptom and receives the probability of the presence of a disease given that symptom. A problem arises when one wishes to get disease probabilities given multiple symptoms. The number of data points needed to do Bayesian calculations on multiple simultaneous symptoms is huge. For example, in a system which handles only single symptoms, if one had a database of 1000 symptoms and 200 diseases, one would need to create 1000 × 200 = 200,000 conditional probabilities, 1000 symptom probabilities, and 200 disease probabilities, for a total of about 200,000 numbers.

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