The select and test algorithm for inference in medical diagnostic reasoning: Implementation and evaluation in clinical psychiatry

作者: D. A. Irosh P. Fernando , Frans A. Henskens

DOI: 10.1109/ICIS.2016.7550738

关键词: CognitionTest algorithmComputer scienceArtificial intelligenceAlgorithm designMachine learningModel-based reasoningMatching (statistics)InferenceTest (assessment)Data miningProcess (engineering)

摘要: Clinical diagnostic reasoning involves an informed search for clinical information driven by hypotheses. This is then followed matching the elicited with criteria each differential diagnosis resulting in conclusions. The existing approaches to were limited their capabilities adequately covering this process, particularly arriving at As a solution, paper presents previously published Select and Test (ST) algorithm that enhanced technique known as orthogonal vector projection method, which used more efficiently effectively implementation of along knowledgebase psychiatry has been described accuracy have demonstrated evaluating it using actual patient data.

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