Prediction on heart disease using multilayer neural network / Lily Syahira Sabrina Ab Rahman
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 de...
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my.uitm.ir.697032022-11-03T07:18:46Z https://ir.uitm.edu.my/id/eprint/69703/ Prediction on heart disease using multilayer neural network / Lily Syahira Sabrina Ab Rahman Ab Rahman, Lily Syahira Sabrina 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 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. 2017-01 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/69703/1/69703.pdf Prediction on heart disease using multilayer neural network / Lily Syahira Sabrina Ab Rahman. (2017) Degree thesis, thesis, Universiti Teknologi MARA, Terengganu. |
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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 Ab Rahman, Lily Syahira Sabrina Prediction on heart disease using multilayer neural network / Lily Syahira Sabrina Ab Rahman |
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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. |
format |
Thesis |
author |
Ab Rahman, Lily Syahira Sabrina |
author_facet |
Ab Rahman, Lily Syahira Sabrina |
author_sort |
Ab Rahman, Lily Syahira Sabrina |
title |
Prediction on heart disease using multilayer neural network / Lily Syahira Sabrina Ab Rahman |
title_short |
Prediction on heart disease using multilayer neural network / Lily Syahira Sabrina Ab Rahman |
title_full |
Prediction on heart disease using multilayer neural network / Lily Syahira Sabrina Ab Rahman |
title_fullStr |
Prediction on heart disease using multilayer neural network / Lily Syahira Sabrina Ab Rahman |
title_full_unstemmed |
Prediction on heart disease using multilayer neural network / Lily Syahira Sabrina Ab Rahman |
title_sort |
prediction on heart disease using multilayer neural network / lily syahira sabrina ab rahman |
publishDate |
2017 |
url |
https://ir.uitm.edu.my/id/eprint/69703/1/69703.pdf https://ir.uitm.edu.my/id/eprint/69703/ |
_version_ |
1748706027380932608 |
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13.251813 |