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Oct 19, 2020 (publication date) through Nov 22, 2024
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Publication Name
World Journal of Psychiatry
ISSN
2220-3206
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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
| For: | Byeon H. Development of a depression in Parkinson's disease prediction model using machine learning. World J Psychiatr 2020; 10(10): 234-244 [PMID: 33134114 DOI: 10.5498/wjp.v10.i10.234] |
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| URL: | https://www.wjgnet.com/2220-3206/full/v10/i10/234.htm |
| Number | Citing Articles |
| 1 |
Haewon Byeon. Screening dementia and predicting high dementia risk groups using machine learning. World Journal of Psychiatry 2022; 12(2): 204-211 doi: 10.5498/wjp.v12.i2.204
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| 2 |
Kaixin Dou, Jiangnan Ma, Xue Zhang, Wanda Shi, Mingzhu Tao, Anmu Xie. Multi-predictor modeling for predicting early Parkinson’s disease and non-motor symptoms progression. Frontiers in Aging Neuroscience 2022; 14 doi: 10.3389/fnagi.2022.977985
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| 3 |
Hessa Alfalahi, Sofia B. Dias, Ahsan H. Khandoker, Kallol Ray Chaudhuri, Leontios J. Hadjileontiadis. A scoping review of neurodegenerative manifestations in explainable digital phenotyping. npj Parkinson's Disease 2023; 9(1) doi: 10.1038/s41531-023-00494-0
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| 4 |
Khalid Orayj, Tahani Almeleebia, Easwaran Vigneshwaran, Sultan Alshahrani, Sirajudeen. S. Alavudeen, Wael Alghamdi. Trend of recognizing depression symptoms and antidepressants use in newly diagnosed Parkinson's disease: Population‐based study. Brain and Behavior 2021; 11(8) doi: 10.1002/brb3.2228
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| 5 |
Baile Ning, Zhifang Wang, Qian Wu, Qiyue Deng, Qing Yang, Jing Gao, Wen Fu, Ying Deng, Bingxin Wu, Xichang Huang, Jilin Mei, Wenbin Fu. Acupuncture inhibits autophagy and repairs synapses by activating the mTOR pathway in Parkinson’s disease depression model rats. Brain Research 2023; 1808: 148320 doi: 10.1016/j.brainres.2023.148320
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| 6 |
Saraswati Patil, Sangita Jaybhaye, Sujal Bokariya, Pranav Jain, Siddhi Phapale, Tejas Hande, A.C. Sumathi, N. Yuvaraj, N.H. Ghazali. Parkinson’s Disease Prediction System in Machine Learning. ITM Web of Conferences 2023; 56: 05002 doi: 10.1051/itmconf/20235605002
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| 7 |
Anastasiia D. Shkodina, Kateryna A. Tarianyk, Mykhaylo Yu Delva, Azmat Ali Khan, Abdul Malik, Sabiha Fatima, Athanasios Alexiou, Md. Habibur Rahman, Marios Papadakis. Influence of sleep quality, excessive daytime sleepiness, circadian features and motor subtypes on depressive symptoms in Parkinson's disease. Sleep Medicine 2025; 125: 57 doi: 10.1016/j.sleep.2024.11.024
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| 8 |
Zhifang Wang, Menglin Kou, Qiyue Deng, Haotian Yu, Jilin Mei, Jing Gao, Wen Fu, Baile Ning. Acupuncture activates IRE1/XBP1 endoplasmic reticulum stress pathway in Parkinson's disease model rats. Behavioural Brain Research 2024; 462: 114871 doi: 10.1016/j.bbr.2024.114871
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| 9 |
Min Seong Kim, Hyesoo Kim, Gabsang Lee. Precision Medicine in Parkinson's Disease Using Induced Pluripotent Stem Cells. Advanced Healthcare Materials 2024; 13(21) doi: 10.1002/adhm.202303041
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| 10 |
Arivarasi A., Alagiri Govindasamy, Sathiya Narayanan S.. Principles and Applications of Socio-Cognitive and Affective Computing. Advances in Computational Intelligence and Robotics 2022; : 130 doi: 10.4018/978-1-6684-3843-5.ch009
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| 11 |
Juntao Tan, Zhengguo Xu, Yuxin He, Lingqin Zhang, Shoushu Xiang, Qian Xu, Xiaomei Xu, Jun Gong, Chao Tan, Langmin Tan. A web-based novel prediction model for predicting depression in elderly patients with coronary heart disease: A multicenter retrospective, propensity-score matched study. Frontiers in Psychiatry 2022; 13 doi: 10.3389/fpsyt.2022.949753
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| 12 |
Yumeng Yan, Yiqian Du, Xue Li, Weiwei Ping, Yunqi Chang. Physical function, ADL, and depressive symptoms in Chinese elderly: Evidence from the CHARLS. Frontiers in Public Health 2023; 11 doi: 10.3389/fpubh.2023.1017689
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| 13 |
Ahmed Hammed Ayyal, Sadik Kamel Gharghan, Ammar Hussein Mutlag. An intelligent system for monitoring and predicting Parkinson’s disease: A review. THE FIFTH SCIENTIFIC CONFERENCE FOR ELECTRICAL ENGINEERING TECHNIQUES RESEARCH (EETR2024) 2024; 3232: 020052 doi: 10.1063/5.0236240
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| 14 |
Rakesh Kumar, Meenu Gupta, Simarpreet Singh. Early Prediction of Parkinson’s Disease using Multiple SVM Classifiers. 2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS) 2023; : 37 doi: 10.1109/ICSCSS57650.2023.10169162
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| 15 |
Hung Viet Nguyen, Haewon Byeon. Prediction of Parkinson’s Disease Depression Using LIME-Based Stacking Ensemble Model. Mathematics 2023; 11(3): 708 doi: 10.3390/math11030708
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| 16 |
Md Belal Bin Heyat, Faijan Akhtar, Farwa Munir, Arshiya Sultana, Abdullah Y. Muaad, Ijaz Gul, Mohamad Sawan, Waseem Asghar, Sheikh Muhammad Asher Iqbal, Atif Amin Baig, Isabel de la Torre Díez, Kaishun Wu. Unravelling the complexities of depression with medical intelligence: exploring the interplay of genetics, hormones, and brain function. Complex & Intelligent Systems 2024; 10(4): 5883 doi: 10.1007/s40747-024-01346-x
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| 17 |
Haewon Byeon. Developing a nomogram for predicting the depression of senior citizens living alone while focusing on perceived social support. World Journal of Psychiatry 2021; 11(12): 1314-1327 doi: 10.5498/wjp.v11.i12.1314
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| 18 |
Sweta Bhadra, Chandan Jyoti Kumar. An insight into diagnosis of depression using machine learning techniques: a systematic review. Current Medical Research and Opinion 2022; 38(5): 749 doi: 10.1080/03007995.2022.2038487
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| 19 |
Haewon Byeon. Predicting the Severity of Parkinson’s Disease Dementia by Assessing the Neuropsychiatric Symptoms with an SVM Regression Model. International Journal of Environmental Research and Public Health 2021; 18(5): 2551 doi: 10.3390/ijerph18052551
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| 20 |
Naresh Alapati, N. Anusha, P Joharika, N. Jenny Jerusha, P Tanuja. Prediction of Parkinson's Disease using Machine Learning. 2023 Second International Conference on Electronics and Renewable Systems (ICEARS) 2023; : 1357 doi: 10.1109/ICEARS56392.2023.10085443
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