Deep Learning–Assisted Gait Parameter Assessment for Neurodegenerative Diseases: Model Development and Validation

Journals

1. Ding H, Feng X, Yang Q, Yang Y, Zhu S, Ji X, Kang Y, Shen J, Zhao M, Xu S, Ning G, Xu Y. A risk prediction model for efficient intubation in the emergency department: A 4‐year single‐center retrospective analysis. Journal of the American College of Emergency Physicians Open 2024;5(3) View
2. Mazurek K, Barnard L, Botha H, Christianson T, Graff-Radford J, Petersen R, Vemuri P, Windham B, Jones D, Ali F. A validation study demonstrating portable motion capture cameras accurately characterize gait metrics when compared to a pressure-sensitive walkway. Scientific Reports 2024;14(1) View
3. Obuchi S, Kojima M, Suzuki H, Garbalosa J, Imamura K, Ihara K, Hirano H, Sasai H, Fujiwara Y, Kawai H. Artificial intelligence detection of cognitive impairment in older adults during walking. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring 2024;16(3) View
4. Yin W, Zhu W, Gao H, Niu X, Shen C, Fan X, Wang C. Gait analysis in the early stage of Parkinson’s disease with a machine learning approach. Frontiers in Neurology 2024;15 View