A coarse-to-fine machine-learning framework for identifying functional connectivity markers of cognitive impairment in Parkinson's disease.

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Title: A coarse-to-fine machine-learning framework for identifying functional connectivity markers of cognitive impairment in Parkinson's disease.
Authors: Chien CY; Department of Neurology, College of Medicine, National Cheng Kung University Hospital, National Cheng Kung University, 138 Sheng Li Road, Tainan, 704, Taiwan.; Department of Biomedical Engineering, College of Engineering, National Cheng Kung University, Tainan, Taiwan., Lee TL; Department of Neurology, College of Medicine, National Cheng Kung University Hospital, National Cheng Kung University, 138 Sheng Li Road, Tainan, 704, Taiwan.; Department of Biomedical Engineering, College of Engineering, National Cheng Kung University, Tainan, Taiwan., Lin TY; Department of Neurology, College of Medicine, National Cheng Kung University Hospital, National Cheng Kung University, 138 Sheng Li Road, Tainan, 704, Taiwan., Yu RL; Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan., Lin CK; Department of Neurology, College of Medicine, National Cheng Kung University Hospital, National Cheng Kung University, 138 Sheng Li Road, Tainan, 704, Taiwan. cxl45@mail.ncku.edu.tw.; Department of Biomedical Engineering, College of Engineering, National Cheng Kung University, Tainan, Taiwan. cxl45@mail.ncku.edu.tw.; Medical Device Innovation Center, National Cheng Kung University, Tainan, Taiwan. cxl45@mail.ncku.edu.tw.
Source: Medical & biological engineering & computing [Med Biol Eng Comput] 2026 Jul 11. Date of Electronic Publication: 2026 Jul 11.
Publication Type: Journal Article
Journal Info: Publisher: Springer Country of Publication: United States NLM ID: 7704869 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1741-0444 (Electronic) Linking ISSN: 01400118 NLM ISO Abbreviation: Med Biol Eng Comput Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1741-0444
DOI:10.1007/s11517-026-03619-8