Classification of fallers in Parkinson's disease through machine learning based feature analysis.

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Title: Classification of fallers in Parkinson's disease through machine learning based feature analysis.
Authors: Kim M; Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul, Korea.; Medical AI Research Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Korea., Kim S; Department of Neurology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea., Chung M; Medical AI Research Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Korea.; Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.; Department of Data Convergence and Future Medicine, Sungkyunkwan University School of Medicine, Seoul, Korea., Cho JW; Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.; Neuroscience Center, Samsung Medical Center, Seoul, Korea., Yoo H; Medical AI Research Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Korea. waihjei11@gmail.com.; Department of Bio-Mechatronic Engineering, Sungkyunkwan University College of Biotechnology and Bioengineering, Gyeonggi, Korea. waihjei11@gmail.com., Youn J; Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. genian@skku.edu.; Neuroscience Center, Samsung Medical Center, Seoul, Korea. genian@skku.edu.
Source: NPJ Parkinson's disease [NPJ Parkinsons Dis] 2026 Apr 12; Vol. 12 (1). Date of Electronic Publication: 2026 Apr 12.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: United States NLM ID: 101675390 Publication Model: Electronic Cited Medium: Print ISSN: 2373-8057 (Print) Linking ISSN: 23738057 NLM ISO Abbreviation: NPJ Parkinsons Dis Subsets: PubMed not MEDLINE
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  Data: <searchLink fieldCode="AU" term="%22Kim+M%22">Kim M</searchLink>; Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul, Korea.; Medical AI Research Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Kim+S%22">Kim S</searchLink>; Department of Neurology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Chung+M%22">Chung M</searchLink>; Medical AI Research Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Korea.; Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.; Department of Data Convergence and Future Medicine, Sungkyunkwan University School of Medicine, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Cho+JW%22">Cho JW</searchLink>; Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.; Neuroscience Center, Samsung Medical Center, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Yoo+H%22">Yoo H</searchLink>; Medical AI Research Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Korea. waihjei11@gmail.com.; Department of Bio-Mechatronic Engineering, Sungkyunkwan University College of Biotechnology and Bioengineering, Gyeonggi, Korea. waihjei11@gmail.com.<br /><searchLink fieldCode="AU" term="%22Youn+J%22">Youn J</searchLink>; Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. genian@skku.edu.; Neuroscience Center, Samsung Medical Center, Seoul, Korea. genian@skku.edu.
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        Value: 10.1038/s41531-026-01343-6
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