Advances in machine learning for the diagnosis of Pakinson's disease
10.3969/j.issn.1005-202X.2024.05.016
- VernacularTitle:机器学习用于帕金森病诊断的研究进展
- Author:
Cheng SHI
1
,
2
;
Xufeng YAO
Author Information
1. 上海理工大学健康科学与工程学院,上海 200093
2. 上海健康医学院医学影像学院,上海 201318
- Keywords:
Parkinson's disease;
machine learning;
intelligent diagnosis;
review
- From:
Chinese Journal of Medical Physics
2024;41(5):640-645
- CountryChina
- Language:Chinese
-
Abstract:
Parkinson's disease(PD)is the second most common neurodegenerative disease after Alzheimer's disease,and the early diagnosis and intervention are crucial for patients.The review focuses on machine learning for intelligent diagnosis of PD.The common machine learning algorithms in PD diagnosis,specifically convolutional neural networks and long short-term memory networks,are introduced,and their applications in medical image analysis and motor behavior analysis are discussed in details.By comparing relevant domestic and international researches,the advantages and disadvantages of using different imaging and kinematic data for PD diagnosis are analyzed.Finally,the review summarizes and presents a prospect for the application of machine learning in PD diagnosis.
