Prediction on heart disease using multilayer neural network / Lily Syahira Sabrina Ab Rahman

• Main Author: Ab Rahman, Lily Syahira Sabrina
• Format: Thesis
• Language: English
• Published: 2017
• Subjects: Instruments and machines; Electronic Computers. Computer Science; Evolutionary programming (Computer science). Genetic algorithms; Computer software; Application program interfaces; Application software; Configuration management; Development. UML (Computer science); Software measurement; Neural networks (Computer science); Database management
• Online Access: https://ir.uitm.edu.my/id/eprint/69703/1/69703.pdf; https://ir.uitm.edu.my/id/eprint/69703/

The early detection of heart disease is vital to avoid sudden death. There are several symptoms that are familiar to heart disease patients by analyzing the symptoms and assisted by specific device, doctors would be able to conform the heart disease. Since the conventional method of heart disease detection is quite tedious, the automatic detection is proposed. In order to automate the early detection an adequate algorithm is needed. The algorithm must be able to receive input of patient’s details, and generate the predicted result. Therefore this study is proposed to implement multilayer neural network in producing the heart disease prediction. The predictions are evaluated by the accuracy testing and the result is 50%, this is because the range of certain criteria is not defined yet.