Enhanced diagnosing patients suspected of sarcoidosis using a hybrid support vector regression model with bald eagle and chimp optimizers
Searching for a reliable indicator of treatment response in sarcoidosis remains a challenge. The use of the soluble interleukin 2 receptor (sIL-2R) as a measure of disease activity has been proposed by researchers. A machine learning model was aimed to be developed in this study to predict sIL-2R le...
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| Language: | English |
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PeerJ Inc.
2024-12-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-2455.pdf |
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| author | Guogang Xie Hani Attar Ayat Alrosan Sally Mohammed Farghaly Abdelaliem Amany Anwar Saeed Alabdullah Mohanad Deif |
| author_facet | Guogang Xie Hani Attar Ayat Alrosan Sally Mohammed Farghaly Abdelaliem Amany Anwar Saeed Alabdullah Mohanad Deif |
| author_sort | Guogang Xie |
| collection | DOAJ |
| description | Searching for a reliable indicator of treatment response in sarcoidosis remains a challenge. The use of the soluble interleukin 2 receptor (sIL-2R) as a measure of disease activity has been proposed by researchers. A machine learning model was aimed to be developed in this study to predict sIL-2R levels based on a patient’s serum angiotensin-converting enzyme (ACE) levels, potentially aiding in lung function evaluation. A novel forecasting model (SVR-BE-CO) for sIL-2R prediction is introduced, which combines support vector regression (SVR) with a hybrid optimization model (BES-CO); The hybrid optimization model composed of Bald Eagle Optimizer (BES) and Chimp Optimizer (CO) model. In this forecasting model, the hyper-parameters of the SVR model are optimized by the BES-CO hybrid optimization model, ultimately improving the accuracy of the predicted sIL-2R values. The hybrid forecasting model SVR-BE-CO model was evaluated against various forecasting methods, including Hybrid SVR with Firefly Algorithm (SVR-FFA), decision tree (DT), SVR with Gray Wolf Optimization (SVR-GWO) and random forest (RF). It was demonstrated that the hybrid SVR-BE-CO model surpasses all other methods in terms of accuracy. |
| format | Article |
| id | doaj-art-d1d02aba838f42b4a410027c61f60d49 |
| institution | Kabale University |
| issn | 2376-5992 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj-art-d1d02aba838f42b4a410027c61f60d492024-12-07T15:05:08ZengPeerJ Inc.PeerJ Computer Science2376-59922024-12-0110e245510.7717/peerj-cs.2455Enhanced diagnosing patients suspected of sarcoidosis using a hybrid support vector regression model with bald eagle and chimp optimizersGuogang Xie0Hani Attar1Ayat Alrosan2Sally Mohammed Farghaly Abdelaliem3Amany Anwar Saeed Alabdullah4Mohanad Deif5Department of Respiratory and Critical Care Medicine, Shanghai General Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, ChinaDepartment of Electrical Engineering, Zarqa University, Zarqa, JordanSchool of Computing, Skyline University, Sharjah, United Arab EmiratesDepartment of Nursing Management and Education, Princess Nourah bint Abdulrahman, Riyadh, Saudi ArabiaDepartment of Maternity and Pediatric Nursing, College of Nursing, Princess Nourah bint Abdulrahman University, Riyadh, Saudi ArabiaDepartment of Artificial Intelligence, College of Information Technology, Misr University for Science & Technology, Cairo, EgyptSearching for a reliable indicator of treatment response in sarcoidosis remains a challenge. The use of the soluble interleukin 2 receptor (sIL-2R) as a measure of disease activity has been proposed by researchers. A machine learning model was aimed to be developed in this study to predict sIL-2R levels based on a patient’s serum angiotensin-converting enzyme (ACE) levels, potentially aiding in lung function evaluation. A novel forecasting model (SVR-BE-CO) for sIL-2R prediction is introduced, which combines support vector regression (SVR) with a hybrid optimization model (BES-CO); The hybrid optimization model composed of Bald Eagle Optimizer (BES) and Chimp Optimizer (CO) model. In this forecasting model, the hyper-parameters of the SVR model are optimized by the BES-CO hybrid optimization model, ultimately improving the accuracy of the predicted sIL-2R values. The hybrid forecasting model SVR-BE-CO model was evaluated against various forecasting methods, including Hybrid SVR with Firefly Algorithm (SVR-FFA), decision tree (DT), SVR with Gray Wolf Optimization (SVR-GWO) and random forest (RF). It was demonstrated that the hybrid SVR-BE-CO model surpasses all other methods in terms of accuracy.https://peerj.com/articles/cs-2455.pdfSarcoidosisBald eagle searchSoluble IL-2 receptorAngiotensin converting enzymeChimp OptimizerMachine learing |
| spellingShingle | Guogang Xie Hani Attar Ayat Alrosan Sally Mohammed Farghaly Abdelaliem Amany Anwar Saeed Alabdullah Mohanad Deif Enhanced diagnosing patients suspected of sarcoidosis using a hybrid support vector regression model with bald eagle and chimp optimizers PeerJ Computer Science Sarcoidosis Bald eagle search Soluble IL-2 receptor Angiotensin converting enzyme Chimp Optimizer Machine learing |
| title | Enhanced diagnosing patients suspected of sarcoidosis using a hybrid support vector regression model with bald eagle and chimp optimizers |
| title_full | Enhanced diagnosing patients suspected of sarcoidosis using a hybrid support vector regression model with bald eagle and chimp optimizers |
| title_fullStr | Enhanced diagnosing patients suspected of sarcoidosis using a hybrid support vector regression model with bald eagle and chimp optimizers |
| title_full_unstemmed | Enhanced diagnosing patients suspected of sarcoidosis using a hybrid support vector regression model with bald eagle and chimp optimizers |
| title_short | Enhanced diagnosing patients suspected of sarcoidosis using a hybrid support vector regression model with bald eagle and chimp optimizers |
| title_sort | enhanced diagnosing patients suspected of sarcoidosis using a hybrid support vector regression model with bald eagle and chimp optimizers |
| topic | Sarcoidosis Bald eagle search Soluble IL-2 receptor Angiotensin converting enzyme Chimp Optimizer Machine learing |
| url | https://peerj.com/articles/cs-2455.pdf |
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