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November 1972

Three Computer Diagnosis Methods Compared

Author Affiliations

New York
From the biostatistics (Dr. Fleiss) and evaluation (Drs. Spitzer and Endicott) sections, Biometrics Research, New York State Department of Mental Hygiene; the New York State Psychiatric Institute (Drs. Fleiss, Spitzer, and Endicott); the departments of biostatistics (Dr. Fleiss) and psychiatry (Drs. Spitzer and Endicott), Columbia University; and the Department of Psychology, New York University, New York (Dr. Cohen).

Arch Gen Psychiatry. 1972;27(5):643-649. doi:10.1001/archpsyc.1972.01750290057011

Three methods for generating psychiatric diagnoses by computer are compared on measures of agreement between computer and clinical diagnoses made on actual samples of cases. Rules for two of the methods, Bayes and discriminant function classification, were derived from characteristics of subjects in a developmental sample. Rules for the third method, DIAGNO II—an example of the logical decision tree approach to differential diagnosis—had been derived a priori.

The three methods performed equally well on a cross-validation sample drawn from the same population as the developmental sample. DIAGNO II performed most accurately on a cross-validation sample from a new population. Reasons are given why, at the present time, a logical decision tree method such as DIAGNO II is preferable to the Bayes and discriminant function methods for computer diagnosis.