The authors describe the general organization of an expert system (LITO 2) for liver disease diagnosis. A frame-like structure is adopted to represent the knowledge of the domain. A structured organization of diagnostic hypotheses is used allowing the system to focus its diagnostic reasoning: preliminary hypotheses, related to general groups of diseases are tried at first on the basis of clinical data, and their consistency is further assessed by a set of laboratory tests. The accepted hypotheses are then refined by new data gathering. Explanation mechanisms allow the user to evaluate the adequacy of the knowledge and to verify the reasoning path followed by the system.

EXPERT SYSTEM FOR LIVER DISEASE DIAGNOSIS (LITO 2) / C. Cravetto; Leonardo Lesmo; Rosa Massa Rolandino; Gianpaolo Molino; Pietro Torasso. - -(1985), pp. 330-334. ((Intervento presentato al convegno Ninth Annual Symposium on Computer Applications in Medical Care tenutosi a Baltimore, MD, USA nel November 3 - 5, 1985.

EXPERT SYSTEM FOR LIVER DISEASE DIAGNOSIS (LITO 2)

LESMO, Leonardo;MOLINO, Gianpaolo;TORASSO, Pietro
1985

Abstract

The authors describe the general organization of an expert system (LITO 2) for liver disease diagnosis. A frame-like structure is adopted to represent the knowledge of the domain. A structured organization of diagnostic hypotheses is used allowing the system to focus its diagnostic reasoning: preliminary hypotheses, related to general groups of diseases are tried at first on the basis of clinical data, and their consistency is further assessed by a set of laboratory tests. The accepted hypotheses are then refined by new data gathering. Explanation mechanisms allow the user to evaluate the adequacy of the knowledge and to verify the reasoning path followed by the system.
Ninth Annual Symposium on Computer Applications in Medical Care
Baltimore, MD, USA
November 3 - 5, 1985
-
330
334
http://www.ncbi.nlm.nih.gov/pmc/issues/173474/
Computer Aided Diagnosis; Artificial Intelligence; Hepatology
C. Cravetto; Leonardo Lesmo; Rosa Massa Rolandino; Gianpaolo Molino; Pietro Torasso
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/109264
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