Computer
Introduction to the theory of neural computation
Introduction to the theory of neural computation
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Fuzzy logic, neural networks, and soft computing
Communications of the ACM
An introduction to genetic algorithms
An introduction to genetic algorithms
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
Practical genetic algorithms
Survey of utilisation of fuzzy technology in medicine and healthcare
Fuzzy Sets and Systems - Special issue on clustering and learning
Fundamentals of Artificial Neural Networks
Fundamentals of Artificial Neural Networks
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Genetic Programming III: Darwinian Invention & Problem Solving
Genetic Programming III: Darwinian Invention & Problem Solving
Nonlinear Biomedical Signal Processing: Fuzzy Logic, Neural Networks, and New Algorithms
Nonlinear Biomedical Signal Processing: Fuzzy Logic, Neural Networks, and New Algorithms
Computers and Biomedical Research
Evolution in Medical Decision Making
Journal of Medical Systems
Neurofuzzy Classification of the Effect of Diabetes Mellitus on Carotid Artery
Journal of Medical Systems
Model-free functional MRI analysis based on unsupervised clustering
Journal of Biomedical Informatics
Evolutionary Computation
Combining Neural Network and Genetic Algorithm for Prediction of Lung Sounds
Journal of Medical Systems
Artificial Intelligence in Medicine
Fuzzy classification by fuzzy labeled neural gas
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
Advanced fuzzy cellular neural network: Application to CT liver images
Artificial Intelligence in Medicine
A markov chain framework for the simple genetic algorithm
Evolutionary Computation
Adaptive neuro-fuzzy inference systems for analysis of internal carotid arterial Doppler signals
Computers in Biology and Medicine
IEEE Transactions on Information Technology in Biomedicine
A novel large-memory neural network as an aid in medical diagnosis applications
IEEE Transactions on Information Technology in Biomedicine
A fuzzy logic based-method for prognostic decision making in breast and prostate cancers
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
Survey on the use of smart and adaptive engineering systems in medicine
Artificial Intelligence in Medicine
Use of genetic algorithms for neural networks to predict community-acquired pneumonia
Artificial Intelligence in Medicine
Evolving connectionist systems for knowledge discovery from gene expression data of cancer tissue
Artificial Intelligence in Medicine
Artificial Intelligence in Medicine
Rule-base derivation for intensive care ventilator control using ANFIS
Artificial Intelligence in Medicine
Artificial Intelligence in Medicine
Fuzzy methods in tremor assessment, prediction, and rehabilitation
Artificial Intelligence in Medicine
Neuro-fuzzy closed-loop control of depth of anaesthesia
Artificial Intelligence in Medicine
A survey of fuzzy logic monitoring and control utilisation in medicine
Artificial Intelligence in Medicine
Neural networks versus genetic algorithms as medical classifiers
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation - Volume Part I
An advanced scatter search design for skull-face overlay in craniofacial superimposition
Expert Systems with Applications: An International Journal
A GMDH-based fuzzy modeling approach for constructing TS model
Fuzzy Sets and Systems
Soft approaches to information access on the Web: An introduction to the special issue
Information Processing and Management: an International Journal
A meta-cognitive sequential learning algorithm for neuro-fuzzy inference system
Applied Soft Computing
Design of a Fuzzy-based Decision Support System for Coronary Heart Disease Diagnosis
Journal of Medical Systems
Predicting the impact of hospital health information technology adoption on patient satisfaction
Artificial Intelligence in Medicine
Soft computing techniques in ensemble precipitation nowcast
Applied Soft Computing
Expert Systems with Applications: An International Journal
An organ allocation system for liver transplantation based on ordinal regression
Applied Soft Computing
Review: Knowledge discovery in medicine: Current issue and future trend
Expert Systems with Applications: An International Journal
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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. The aim of this paper is to introduce briefly the various SC methodologies and to present various applications in medicine between the years 2000 and 2008. The scope is to demonstrate the possibilities of applying SC to medicine-related problems. The recent published knowledge about use of SC in medicine is researched in MEDLINE. This study detects which methodology or methodologies of SC are used frequently together to solve the special problems of medicine. According to MEDLINE database searches, the rates of preference of SC methodologies in medicine were found as 68% of FL-NN, 27% of NN-GA and 5% of FL-GA. So far, FL-NN methodology was significantly used in medicine. The rates of using FL-NN in clinical science, diagnostic science and basic science were found as %83, %71 and %48, respectively. On the other hand NN-GA and FL-GA methodologies were mostly preferred by basic science of medicine. Another message emerging from this survey is that the number of papers which used NN-GA methodology has continuously risen until today. Also search results put the case clearly that FL-GA methodology has not applied well enough to medicine yet. Undeniable interest in studying SC methodologies in genetics, physiology, radiology, cardiology, and neurology disciplines proves that studying SC is very fruitful in these disciplines and it is expected that future researches in medicine will use SC more than it is used today to solve more complex problems.