Soft computing in medicine

Yardimci A.

APPLIED SOFT COMPUTING, cilt.9, sa.3, ss.1029-1043, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 9 Sayı: 3
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1016/j.asoc.2009.02.003
  • Dergi Adı: APPLIED SOFT COMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1029-1043
  • Anahtar Kelimeler: Soft computing, Fuzzy-neural systems, Fuzzy-genetic algorithms, Neural-genetic algorithms, Medicine, ARTIFICIAL NEURAL-NETWORKS, PROBABILISTIC BOOLEAN NETWORKS, FUZZY INFERENCE SYSTEMS, GENE-EXPRESSION DATA, MOLECULAR DESCRIPTORS, REGULATORY NETWORKS, DECISION-MAKING, RULE-BASE, ALGORITHM, CANCER
  • Akdeniz Üniversitesi Adresli: Evet

Özet

Soft computing (SC) is not a new term; we have gotten used to reading and hearing about it daily. Nowadays, the term is used often in computer science and information technology. It is possible to define SC in different ways. Nonetheless, SC is a consortium of methodologies which works synergistically and provides, in one form or another, flexible information processing capability for handling real life ambiguous situations. Its aim is to exploit the tolerance for imprecision, uncertainty, approximate reasoning and partial truth in order to achieve tractability, robustness and low-cost solutions. SC includes fuzzy logic (FL), neural networks (NNs), and genetic algorithm (GA) methodologies. SC combines these methodologies as FL and NN (FL-NN), NN and GA (NN-GA) and FL and GA (FL-GA). Recent years have witnessed the phenomenal growth of bio-informatics and medical informatics by using computational techniques for interpretation and analysis of biological and medical data. Among the large number of computational techniques used, SC, which incorporates neural networks, evolutionary computation, and fuzzy systems, provides unmatched utility because of its demonstrated strength in handling imprecise information and providing novel solutions to hard problems.