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Updated: Jul 11, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Simple algorithms for predicting psychotropic drugs assigned to psychiatric inpatients
Abstract:
The ability of simple algorithms, primarily diagnostic, to assign classes of psychotropic drugs to psychiatric inpatients in agreement with actual clinical decisions was investigated. Overall agreement (hit-rates) ranging from 48 to 65 percent were found across four major drug groups: major tranquilizer, antidepressant, minor tranquilizer, and no psychotropic drug. These hit-rates may be compared with multivariate formulae developed in earlier studies that achieved hit-rates ranging from 62 to 77 percent. Agreement among clinicians (about 70 percent) appears to be the limiting factor in most studies of this type.
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