Case studies on neural networks for prediction in health/diseases problems

Abstract

Human health is one of topics which require minimum error or even zero tolerance error in all research including in computer science research. Classification in health problems is an interesting and ongoing topic research to solve a problem with minimum error result where neural network has become a popular approach in this area. Types and characteristics of data sources selected to make a prediction for seven health disease problems were described in this paper. The summary of the report is expected to be stimulation for next researches interest in selecting a method or a technique which is appropriate with the health problem to solve.