Application of neural networks in early detection and diagnosis of parkinson's disease
Parkinson’s disease (PD) is a chronic neurological progressive disorder caused by lack of the chemical dopamine in the brain. Up to today, there is still no cure or prevention for PD, and usually the disease worsens gradually over time. However, this disease can be controlled with some treatment, es...
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| Format: | Proceeding Paper |
| Language: | English English |
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Institute of Electrical and Electronics Engineers, Inc.
2014
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| Online Access: | http://irep.iium.edu.my/43064/ http://irep.iium.edu.my/43064/1/43064_Application%20of%20neural%20networks.pdf http://irep.iium.edu.my/43064/2/43064_Application%20of%20neural%20networks_SCOPUS.pdf |
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| author | Olanrewaju, Rashidah Funke Sahari, Nur Syarafina Aibinu, Abiodun Musa Hakiem, Nashrul |
| author_facet | Olanrewaju, Rashidah Funke Sahari, Nur Syarafina Aibinu, Abiodun Musa Hakiem, Nashrul |
| author_sort | Olanrewaju, Rashidah Funke |
| building | IIUM Repository |
| collection | Online Access |
| description | Parkinson’s disease (PD) is a chronic neurological progressive disorder caused by lack of the chemical dopamine in the brain. Up to today, there is still no cure or prevention for PD, and usually the disease worsens gradually over time. However, this disease can be controlled with some treatment, especially in the early stage. Hence, this study proposes a method in early detection and diagnosis of PD by using the Multilayer Feedforward Neural Network (MLFNN) with Back-propagation (BP) algorithm. This MLFNN with BP algorithm is simulated using MATLAB software. The dataset information used in this study was taken from the Oxford Parkinson’s Disease Detection Dataset. The output of the network is classified into healthy or PD by using K-Means Clustering algorithm. The performance of this classifier was evaluated based on the three parameters; sensitivity, specificity and accuracy. The result shows that network can be used in diagnosis and detection of PD due to the good performance, which is 83.3% for sensitivity, 63.6% for specificity, and 80% for accuracy. |
| first_indexed | 2025-11-14T16:04:31Z |
| format | Proceeding Paper |
| id | iium-43064 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T16:04:31Z |
| publishDate | 2014 |
| publisher | Institute of Electrical and Electronics Engineers, Inc. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-430642016-12-15T09:02:24Z http://irep.iium.edu.my/43064/ Application of neural networks in early detection and diagnosis of parkinson's disease Olanrewaju, Rashidah Funke Sahari, Nur Syarafina Aibinu, Abiodun Musa Hakiem, Nashrul Q Science (General) Parkinson’s disease (PD) is a chronic neurological progressive disorder caused by lack of the chemical dopamine in the brain. Up to today, there is still no cure or prevention for PD, and usually the disease worsens gradually over time. However, this disease can be controlled with some treatment, especially in the early stage. Hence, this study proposes a method in early detection and diagnosis of PD by using the Multilayer Feedforward Neural Network (MLFNN) with Back-propagation (BP) algorithm. This MLFNN with BP algorithm is simulated using MATLAB software. The dataset information used in this study was taken from the Oxford Parkinson’s Disease Detection Dataset. The output of the network is classified into healthy or PD by using K-Means Clustering algorithm. The performance of this classifier was evaluated based on the three parameters; sensitivity, specificity and accuracy. The result shows that network can be used in diagnosis and detection of PD due to the good performance, which is 83.3% for sensitivity, 63.6% for specificity, and 80% for accuracy. Institute of Electrical and Electronics Engineers, Inc. 2014 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/43064/1/43064_Application%20of%20neural%20networks.pdf application/pdf en http://irep.iium.edu.my/43064/2/43064_Application%20of%20neural%20networks_SCOPUS.pdf Olanrewaju, Rashidah Funke and Sahari, Nur Syarafina and Aibinu, Abiodun Musa and Hakiem, Nashrul (2014) Application of neural networks in early detection and diagnosis of parkinson's disease. In: 2014 International Conference on Cyber and IT Service Management (CITSM), 3rd-6th Nov. 2014, Jakarta, Indonesia. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=7042180& |
| spellingShingle | Q Science (General) Olanrewaju, Rashidah Funke Sahari, Nur Syarafina Aibinu, Abiodun Musa Hakiem, Nashrul Application of neural networks in early detection and diagnosis of parkinson's disease |
| title | Application of neural networks in early detection and diagnosis of parkinson's disease |
| title_full | Application of neural networks in early detection and diagnosis of parkinson's disease |
| title_fullStr | Application of neural networks in early detection and diagnosis of parkinson's disease |
| title_full_unstemmed | Application of neural networks in early detection and diagnosis of parkinson's disease |
| title_short | Application of neural networks in early detection and diagnosis of parkinson's disease |
| title_sort | application of neural networks in early detection and diagnosis of parkinson's disease |
| topic | Q Science (General) |
| url | http://irep.iium.edu.my/43064/ http://irep.iium.edu.my/43064/ http://irep.iium.edu.my/43064/1/43064_Application%20of%20neural%20networks.pdf http://irep.iium.edu.my/43064/2/43064_Application%20of%20neural%20networks_SCOPUS.pdf |