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Evolution in medical decision making.

Matej Sprogar·Mitja Lenic·Silvia Alayon
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Abstract

The classical approach to medical decision making can be limited by the underlying theories. The evolutionary computation is a different concept, which can find many different solutions of the problem. In medicine, this is useful because of different expectations the decision system must face. We implemented a tool for genetic induction of vector decision trees, which are a good choice for a medical decision model because of their simplicity and transparency. The vector decision tree gives multiple classifications in one single pass. Evolutionary development of such trees achieved good results when the results were statistically compared to those of other classical methods. For medical interpretation however a cooperation with doctors is needed to verify the model build.

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AlgorithmsArtificial IntelligenceClinical MedicineDecision Support Systems, ClinicalDecision TreesHumansMedical InformaticsNeoplasmsRecurrenceJournal Article

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BibTeXRIS

Matej Sprogar, Mitja Lenic, Silvia Alayon. 2002. Evolution in medical decision making.. https://doi.org/10.1023/a%3A1016413418549

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