A review of emergent intelligent systems for the detection of Parkinson’s disease
Author:
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering
Link
https://link.springer.com/content/pdf/10.1007/s13534-023-00319-2.pdf
Reference134 articles.
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3. Müller B, Assmus J, Herlofson K, Larsen JP, Tysnes OB. Importance of motor vs. non-motor symptoms for health-related quality of life in early Parkinson’s disease. Parkinsonism Relat Disorders. 2013;19(11):1027–32. https://doi.org/10.1016/j.parkreldis.2013.07.010.
4. Yeoh PSQ, Lai KW, Goh SL, Hasikin K, Hum YC, Tee YK, et al. Emergence of deep learning in knee osteoarthritis diagnosis. Comput Intell Neurosci. 2021. https://doi.org/10.1155/2021/4931437.
5. Lee LS, Chan PK, Wen C, Fung WC, Cheung A, et al. Artificial intelligence in diagnosis of knee osteoarthritis and prediction of arthroplasty outcomes: a review. Arthroplasty. 2022;4:16. https://doi.org/10.1186/s42836-022-00118-7.
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