An Evaluation Of Artificial Neural Network In Predicting The Presence Of Heart Disease
The purpose of this study is to evaluate the application of artificial neural network in predicting the presence of heart disease, particularly the angina in patients that already diagnosed with myocardial infarction. The prediction and detection of angina is important in determining the most approp...
محفوظ في:
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| التنسيق: | أطروحة |
| اللغة: | eng eng |
| منشور في: |
2000
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| الوصول للمادة أونلاين: | https://etd.uum.edu.my/181/1/MOHD_KHALID_BIN_AWANG_-_An_evaluation_of_artificial_neural_network_in_predicting_the_presence_of_hearts_disease.pdf https://etd.uum.edu.my/181/2/1.MOHD_KHALID_BIN_AWANG_-_An_evaluation_of_artificial_neural_network_in_predicting_the_presence_of_hearts_disease.pdf |
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my-uum-etd.1812022-06-07T04:08:22Z An Evaluation Of Artificial Neural Network In Predicting The Presence Of Heart Disease 2000 Mohd Khalid, Awang Sekolah Siswazah Sekolah Siswazah QA76 Computer software The purpose of this study is to evaluate the application of artificial neural network in predicting the presence of heart disease, particularly the angina in patients that already diagnosed with myocardial infarction. The prediction and detection of angina is important in determining the most appropriate form of treatment for these patients. Furthermore, diagnosis and management of angina is important since it can lead to the recurrent of myocardial infarction. The development of the application involves three main phases. The first phase is the development of Myocardial Infarction Management Information System (MIMIS) for data collection and management. Then followed by the second phase, which is the development of Neural Network Simulator (NNS) using back propagation for network training and testing. The final phase is the development of Prediction System (PS) for prediction on new patient’s data. All systems had been developed using Microsoft’s Visual Basics. The data used to train and test the network was provided by Alor Setar General Hospital, Kedah. The best network model produced prediction accuracy of 88.89 percents. Apart from proving the ability of neural network technology in medical diagnosis, this study also shown how the neural network could be integrated into a management information system as a prediction tools. As the pilot project, the application developed could be used as the starting point in building a medical decision support system, particularly in diagnosing the heart disease. 2000 Thesis https://etd.uum.edu.my/181/ https://etd.uum.edu.my/181/1/MOHD_KHALID_BIN_AWANG_-_An_evaluation_of_artificial_neural_network_in_predicting_the_presence_of_hearts_disease.pdf text eng public https://etd.uum.edu.my/181/2/1.MOHD_KHALID_BIN_AWANG_-_An_evaluation_of_artificial_neural_network_in_predicting_the_presence_of_hearts_disease.pdf text eng public masters masters Universiti Utara Malaysia |
| institution |
Universiti Utara Malaysia |
| collection |
UUM ETD |
| language |
eng eng |
| topic |
QA76 Computer software |
| spellingShingle |
QA76 Computer software Mohd Khalid, Awang An Evaluation Of Artificial Neural Network In Predicting The Presence Of Heart Disease |
| description |
The purpose of this study is to evaluate the application of artificial neural network in predicting the presence of heart disease, particularly the angina in patients that already diagnosed with myocardial infarction. The prediction and detection of angina is important in determining the most appropriate form of treatment for these patients. Furthermore, diagnosis and management of angina is important since it can lead to the recurrent of myocardial infarction. The development of the application involves three main phases. The first phase is the development of Myocardial Infarction Management Information System (MIMIS) for data collection and management. Then followed by the second phase, which is the development of Neural Network Simulator (NNS) using
back propagation for network training and testing. The final phase is the development of Prediction System (PS) for prediction on new patient’s data. All systems had been
developed using Microsoft’s Visual Basics. The data used to train and test the network was provided by Alor Setar General Hospital, Kedah. The best network model produced
prediction accuracy of 88.89 percents. Apart from proving the ability of neural network technology in medical diagnosis, this study also shown how the neural network could be integrated into a management information system as a prediction tools. As the pilot project, the application developed could be used as the starting point in building a medical decision support system, particularly in diagnosing the heart disease. |
| format |
Thesis |
| qualification_name |
masters |
| qualification_level |
Master's degree |
| author |
Mohd Khalid, Awang |
| author_facet |
Mohd Khalid, Awang |
| author_sort |
Mohd Khalid, Awang |
| title |
An Evaluation Of Artificial Neural Network In Predicting The Presence Of Heart Disease |
| title_short |
An Evaluation Of Artificial Neural Network In Predicting The Presence Of Heart Disease |
| title_full |
An Evaluation Of Artificial Neural Network In Predicting The Presence Of Heart Disease |
| title_fullStr |
An Evaluation Of Artificial Neural Network In Predicting The Presence Of Heart Disease |
| title_full_unstemmed |
An Evaluation Of Artificial Neural Network In Predicting The Presence Of Heart Disease |
| title_sort |
evaluation of artificial neural network in predicting the presence of heart disease |
| granting_institution |
Universiti Utara Malaysia |
| granting_department |
Sekolah Siswazah |
| publishDate |
2000 |
| url |
https://etd.uum.edu.my/181/1/MOHD_KHALID_BIN_AWANG_-_An_evaluation_of_artificial_neural_network_in_predicting_the_presence_of_hearts_disease.pdf https://etd.uum.edu.my/181/2/1.MOHD_KHALID_BIN_AWANG_-_An_evaluation_of_artificial_neural_network_in_predicting_the_presence_of_hearts_disease.pdf |
| _version_ |
1747826854345048064 |