A survey on use of soft computing methods in medicine

Authors:
Ahmet Yardimci
Affiliations:
Akdeniz University, Vocational School of Technical Sciences, Department of Industrial Automation, Antalya, Turkey
Venue:
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Year:
2007

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Abstract

The objective of this paper is to introduce briefly the various soft computing methodologies and to present various applications in medicine. The scope is to demonstrate the possibilities of applying soft computing to medicine related problems. The recent published knowledge about use of soft computing in medicine is observed from the literature surveyed and reviewed. This study detects which methodology or methodologies of soft computing are used frequently together to solve the special problems of medicine. According to database searches, the rates of preference of soft computing methodologies in medicine are found as 70% of fuzzy logic-neural networks, 27% of neural networks-genetic algorithms and 3% of fuzzy logic-genetic algorithms in our study results. So far, fuzzy logic-neural networks methodology was significantly used in clinical science of medicine. On the other hand neural networks-genetic algorithms and fuzzy logic-genetic algorithms methodologies were mostly preferred by basic science of medicine. The study showed that there is undeniable interest in studying soft computing methodologies in genetics, physiology, radiology, cardiology, and neurology disciplines.