Hypothesis Formation and Evaluation in Medical Diagnosis

Item

Title: en_US Hypothesis Formation and Evaluation in Medical Diagnosis
Creator: en_US Rubin, Ann D.
Date: 2004-10-20T20:07:00Z
Date Available: 2004-10-20T20:07:00Z
Date Issued: en_US 1975-01-01
Identifier: en_US AITR-316
uri: http://hdl.handle.net/1721.1/6919
Abstract: en_US This thesis describes some aspects of a computer system for doing medical diagnosis in the specialized field of kidney disease. Because such a system faces the spectre of combinatorial explosion, this discussion concentrates on heuristics which control the number of concurrent hypotheses and efficient "compiled" representations of medical knowledge. In particular, the differential diagnosis of hematuria (blood in the urine) is discussed in detail. A protocol of a simulated doctor/patient interaction is presented and analyzed to determine the crucial structures and processes involved in the diagnosis procedure. The data structure proposed for representing medical information revolves around elementary hypotheses which are activated when certain disposing of findings, activating hypotheses, evaluating hypotheses locally and combining hypotheses globally is examined for its heuristic implications. The thesis attempts to fit the problem of medical diagnosis into the framework of other Artifcial Intelligence problems and paradigms and in particular explores the notions of pure search vs. heuristic methods, linearity and interaction, local vs. global knowledge and the structure of hypotheses within the world of kidney disease.
Extent: 18997474 bytes; 14991760 bytes
Format: application/postscript; application/pdf
Language: en_US
Relation: en_US AITR-316

Item sets: AI Technical Reports (1964 - 2004)