Parkinson’s Disease Detection Based on Transfer Learning
The process of diagnosing diseases early is one of the most important goals of the tremendous development in artificial intelligence, and Parkinson’s disease is one of the diseases whose symptoms are similar to many other diseases. It is a neurological disease whose symptoms develop slowly, so the...
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| Format: | Article |
| Language: | English |
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Northern Technical University
2024-09-01
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| Series: | NTU Journal of Engineering and Technology |
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| Online Access: | https://journals.ntu.edu.iq/index.php/NTU-JET/article/view/1173 |
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| _version_ | 1849225537689485312 |
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| author | Mohammad Talal Ghazal |
| author_facet | Mohammad Talal Ghazal |
| author_sort | Mohammad Talal Ghazal |
| collection | DOAJ |
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The process of diagnosing diseases early is one of the most important goals of the tremendous development in artificial intelligence, and Parkinson’s disease is one of the diseases whose symptoms are similar to many other diseases. It is a neurological disease whose symptoms develop slowly, so the process of its diagnosis is very important in order to preserve the patient's life. One of the most important symptoms is muscle stiffness as well as slow movement. In this research, a method was developed to detect Parkinson's disease using machine learning, learning transfer techniques were relied upon to extract features from handwriting images that we obtained from the NewHandPD database, and then these images were classified into two categories (Parkinson's disease and non-Parkinson's disease) by KNN classification algorithm, for being accurate and fast in calculations, the results of the training of the INCEPTION-V4 model showed a detection accuracy of up to 93%, as well as an area under the curve of 0.89 with a loss of only 0.2 , where this model can be relied on to diagnose and detect Parkinson's disease with high accuracy.
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| format | Article |
| id | doaj-art-346f8787beb240569cf7d0a7cff1a1fe |
| institution | Kabale University |
| issn | 2788-9971 2788-998X |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Northern Technical University |
| record_format | Article |
| series | NTU Journal of Engineering and Technology |
| spelling | doaj-art-346f8787beb240569cf7d0a7cff1a1fe2025-08-24T13:05:05ZengNorthern Technical UniversityNTU Journal of Engineering and Technology2788-99712788-998X2024-09-013310.56286/ntujet.v3i3.11731174Parkinson’s Disease Detection Based on Transfer LearningMohammad Talal Ghazal0Northern Technical University The process of diagnosing diseases early is one of the most important goals of the tremendous development in artificial intelligence, and Parkinson’s disease is one of the diseases whose symptoms are similar to many other diseases. It is a neurological disease whose symptoms develop slowly, so the process of its diagnosis is very important in order to preserve the patient's life. One of the most important symptoms is muscle stiffness as well as slow movement. In this research, a method was developed to detect Parkinson's disease using machine learning, learning transfer techniques were relied upon to extract features from handwriting images that we obtained from the NewHandPD database, and then these images were classified into two categories (Parkinson's disease and non-Parkinson's disease) by KNN classification algorithm, for being accurate and fast in calculations, the results of the training of the INCEPTION-V4 model showed a detection accuracy of up to 93%, as well as an area under the curve of 0.89 with a loss of only 0.2 , where this model can be relied on to diagnose and detect Parkinson's disease with high accuracy. https://journals.ntu.edu.iq/index.php/NTU-JET/article/view/1173ParkinsonKNN CNNTransfer learningNewHandPD |
| spellingShingle | Mohammad Talal Ghazal Parkinson’s Disease Detection Based on Transfer Learning NTU Journal of Engineering and Technology Parkinson KNN CNN Transfer learning NewHandPD |
| title | Parkinson’s Disease Detection Based on Transfer Learning |
| title_full | Parkinson’s Disease Detection Based on Transfer Learning |
| title_fullStr | Parkinson’s Disease Detection Based on Transfer Learning |
| title_full_unstemmed | Parkinson’s Disease Detection Based on Transfer Learning |
| title_short | Parkinson’s Disease Detection Based on Transfer Learning |
| title_sort | parkinson s disease detection based on transfer learning |
| topic | Parkinson KNN CNN Transfer learning NewHandPD |
| url | https://journals.ntu.edu.iq/index.php/NTU-JET/article/view/1173 |
| work_keys_str_mv | AT mohammadtalalghazal parkinsonsdiseasedetectionbasedontransferlearning |