Using ontologies and probabilistic networks to develop a preventive stroke diagnosis system (PSDS)

Several works identify that ischemic stroke, which is the most prevalent type of stroke with more of 85% of total strokes, is one of the main mortality causes in various countries. In this pathology, is hard to generate a diagnosis until the first symptoms don't appear, and for hence, the preve...

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Bibliographic Details
Main Authors: Rodriguez-Gonzalez, A., Mayer, M. A., Alor-Hernandez, G., Gomez-Berbis, J. M., Cortes-Robles, G., Lemos, A. L.
Format: Conference Proceeding
Language:English
Subjects:
Diabetes
Diseases
Hemorrhaging
Medical diagnostic imaging
Ontologies
Probabilistic logic
Probability
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Summary:Several works identify that ischemic stroke, which is the most prevalent type of stroke with more of 85% of total strokes, is one of the main mortality causes in various countries. In this pathology, is hard to generate a diagnosis until the first symptoms don't appear, and for hence, the preventive diagnosis based on risk factors are generally the best existing tools to prevent this pathology. Several studies treats epidemiological data of the different risk factors but there exists the necessity of an information system that allows knowing if a concrete patient presents a higher risk for suffering a stroke. The aim of this paper is the theoretical design of a system for prevention of stroke using ontologies as a knowledge base and probabilistic inference over the developed ontology in order to know with more certainty if a patient can suffer a stroke.
ISSN:1063-7125
DOI:10.1109/CBMS.2010.6042672