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Artificial Intelligence Approaches to Medical Diagnosis

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dc.contributor.author Rubin, Andee
dc.date.accessioned 2008-04-10T13:30:36Z
dc.date.available 2008-04-10T13:30:36Z
dc.date.issued 1974-03
dc.identifier.uri http://hdl.handle.net/1721.1/41100
dc.description Work reported herein was conducted at the Artificial Intelligence Laboratory, a Massachusetts Institute of Technology research program supported in part by the Advanced Research Projects Agency of the Department of Defense and monitored by the Office of Naval Research under Contract Number N00014-70-A-0362-0005. en
dc.description.abstract The differential diagnosis of hematuria, blood in the urine, is studied from the point of view of identifying crucial structures and processes in medical diagnosis. The thesis attempts to fit the problem of medical diagnosis into the framework of other A.I. problems and paradigms and in particular explores the notions of pure search vs. heuristic methods, linearity and interaction, plausibility and the structure of hypotheses within the world of kidney disease. en
dc.description.sponsorship MIT Artificial Intelligence Laboratory en
dc.language.iso en_US en
dc.publisher MIT Artificial Intelligence Laboratory en
dc.relation.ispartofseries MIT Artificial Intelligence Laboratory Working Papers, WP-65 en
dc.title Artificial Intelligence Approaches to Medical Diagnosis en
dc.type Working Paper en


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