Medical Data Mining and Bioinformatics: SWARM INTELLIGENCE BASED FEATURE SELECTION ALGORITHMS AND CLASSIFIERS FOR GASTRIC CANCER PREDICTION

Recently, it is observed in the research domain of computer science that, data mining has emerged to be an interesting area of research constantly. Furthermore, soft computing offers a remarkable contribution to data mining research, which is used for applications involving design and development of predictive data mining and descriptive data mining. It is exploited to a considerable degree in the healthcare industry, in creating patient – oriented healthcare systems and helping the health experts. Such systems and professionals are employed for systematic utilization of the data and analytics in finding consoles and best practices, which results in better patient care with minimum expenses. Most of the times, Gastric Cancer acquires the fourth position of generic cancer and has become the second biggest reason for mortality due to cancer in the entire world. This forms the motivating force behind this research. This book is aimed at the design and development of novel classifiers depending on data mining techniques for gastric cancer data classification. In addition, novel feature selection techniques are developed for the prediction of gastric cancer.