An aggregation of PRO and CON evidence for medical decision support systems

✍ Scribed by Ludmila Kuncheva

• Publisher: Elsevier Science
• Year: 1993
• Tongue: English
• Weight: 701 KB
• Volume: 23
• Category: Article
• ISSN: 0010-4825
• DOI: 10.1016/0010-4825(93)90090-n

✦ Synopsis

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. PRO and CON evidence Medical decision support Classification accuracy Multi-level classifier Fuzzy neuron Aviation medicine About the Author-LuDMrLn ILIEVA KUNCHEVA graduated from the Higher Institute for Mechanical and Electrical Engineering, Sofia, in 1982. In 1987 she received her Ph.D. degree in the field of Fuzzy Pattern Recognition from the Bulgarian Academy of Sciences. Dr Kuncheva works with a Biomedical Cybernetics group in the Central Laboratory of Bioinstrumentation and Automation, Bulgarian Academy of Sciences. She is a member of the Bulgarian Association for Pattern Recognition and of the Balkanic Union for Fuzzy Systems and Artificial Intelligence.