An aggregation of pro and con evidence for medical decision support systems.
One promising way to increase the classification accuracy of medical decision support systems is to implement heuristic combinations of pattern recognition and artificial intelligence tools. A parallel between "cognition" model and differential diagnostic task is sketched accentuating the aggregation of activating and restraining inputs and corresponding PRO and CON evidence in medicine. On the basis of this paradigm a trainable model of a fuzzy neuron is proposed which resembles some elements from the physician's decision process. An example from aviation medicine is presented which demonstrates the enhanced performance.
Kuncheva
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Central Laboratory of Bioinstrumentation and Automation, Bulgarian Academy of Sciences, Sofia.
D000337:Aerospace Medicine; D001185:Artificial Intelligence; D003658:Decision Making, Computer-Assisted; D003661:Decision Support Techniques; D003936:Diagnosis, Computer-Assisted; D017143:Fuzzy Logic; D008959:Models, Neurological; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated