Application of Perceptron Networks in Recommending Medical Diagnosis

ABSTRACT Artificial intelligence applications in medicine is the major and evolutionary topic in the technology world. Neural networks is an important branch of machine learning which is inspired from biological neural networks. Neural networks are useful in making proper decisions in rational environments with uncertainty. The neural networks perform better computation with high power with the help of the multiple interconnected neurons which act as processing elements. Decision theory along with probabilistic theory gives the good way to make the right decisions. Neural Network systems help in linking the health observations with the health knowledge database to take better decisions for good health. The ability of a neural network to learn by example can be implemented for taking decisions that would increase the rate of providing the better medical care facilities. This paper presents a novel methodology to implement supervised learning networks that is perceptron networks in medical diagnosis for providing such good decisions to the doctors in helping patients by also providing a good health care.