Artificial Neural Networks in Medical Diagnosis

Artificial Neural Networks (ANNs) have become a transformative tool in the field of medical diagnosis, offering the potential to improve accuracy, efficiency, and early detection of diseases.This paper explores the application of ANNs in medical diagnostics, presenting a comprehensive survey of the literature, a detailed description of the proposed diagnosis model, and the experimental results.The discussion extends to future enhancements and potential improvements in this domain.The results of applying the artificial neural networks methodology to acute nephritis diagnosis based upon selected symptoms show abilities of the network to learn the patterns corresponding to symptoms of the person.In this study, the data were obtained from UCI machine learning repository in order to diagnosed diseases.The data is separated into inputs and targets.The targets for the neural network will be identified with 1's as infected and will be identified with 0's as non-infected..