A survey on genetic algorithm based feature selection for disease diagnosis system

摘要: Computer Aided Diagnosis (CAD) has been a rapidly growing, dynamic area of research in medical imaging. In recent years, significant and serious efforts have made towards the development CAD system diagnostic radiology. Machine learning (ML) plays vital role because objects such as organs may not be signified precisely by simple equation therefore pattern recognition essentially involves from examples. order to reduce dimensions dataset increase classification accuracy rate feature selection done. Feature Selection (FS) is an important issue building systems. Evolutionary algorithms are emergent computing methodology. Genetic Algorithm (GA) being heuristic search algorithm generally used detect features for large dimensional datasets. This paper surveys existing literature about GA selection. study also comprises snapshot author's perspective, including variations algorithm, modifications refinements introduced prevent local convergence hybridization with other algorithms. last part paper, some topics within this field listed that considered promising areas future research.