Discovering Medical Knowledge from Data in Patients’ Files
An Individual Patient’s File (IPF) includes information about a patient and the course of his illness over many years. During this period, the doctor, taking permanent care of the patient, puts various data and observations into his IPF. In the paper we propose a kind of probabilistic and statistical analysis of the data stored in collections of IPFs. The collections can be made accessible by means of a medical Semantic Web. The proposed analysis requires the data to be expressed in the form of Bernoulli variables. As a result, it gives us medical hypotheses, with their premises-facts, conclusions and reliabilities. They can be presented in the form of production rules, used in medical Rule-Based Systems for automatic reasoning.
Keywordsindividual patient’s file Bernoulli variable conditional probability statistical analysis medical rule-based system
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