Artificial Intelligence Approaches to Medical Diagnosis

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