作者: D. A. Irosh P. Fernando , Frans A. Henskens
DOI: 10.1109/ICIS.2016.7550738
关键词: Cognition 、 Test algorithm 、 Computer science 、 Artificial intelligence 、 Algorithm design 、 Machine learning 、 Model-based reasoning 、 Matching (statistics) 、 Inference 、 Test (assessment) 、 Data mining 、 Process (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.