Alzheimer's disease digital biomarkers multidimensional landscape and AI model scoping review.

Journal: NPJ digital medicine
Published Date: Jun 16, 2025

Abstract

As digital biomarkers gain traction in Alzheimer's disease (AD) diagnosis, understanding recent advancements is crucial. This review conducts a bibliometric analysis of 431 studies from five online databases: Web of Science, PubMed, Embase, IEEE Xplore, and CINAHL, and provides a scoping review of 86 artificial intelligence (AI) models. Research in this field is supported by 224 grants across 54 disciplines and 1403 institutions in 44 countries, with 2571 contributing researchers. Key focuses include motor activity, neurocognitive tests, eye tracking, and speech analysis. Classical machine learning models dominate AI research, though many lack performance reporting. Of 21 AD-focused models, the average AUC is 0.887, while 45 models for mild cognitive impairment show an average AUC of 0.821. Notably, only 2 studies incorporated external validation, and 3 studies performed model calibration. This review highlights the progress and challenges of integrating digital biomarkers into clinical practice.

Authors

  • Wenhao Qi
    School of Nursing, Hangzhou Normal University, Hangzhou, China.
  • Xiaohong Zhu
    School of Nursing, Hangzhou Normal University, Hangzhou, China.
  • Bin Wang
    State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China; New South Wales Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga 2650, Australia. Electronic address: bin.a.wang@dpi.nsw.gov.au.
  • Yankai Shi
    School of Nursing, Hangzhou Normal University, Hangzhou, China.
  • Chaoqun Dong
    Institute of Materials, École Polytechnique Fédérale de Lausanne, Lausanne, 1015, Switzerland.
  • Shiying Shen
    School of Nursing, Hangzhou Normal University, Hangzhou, China.
  • Jiaqi Li
    Department of Critical Care Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, People's Republic of China.
  • Kun Zhang
    Philosophy Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
  • Yunfan He
    School of International Relations and Public Affairs, Fudan University, Shanghai, People's Republic of China.
  • Mengjiao Zhao
    School of Nursing, Zhejiang Chinese Medical University, Hangzhou, China.
  • Shiyan Yao
    School of Nursing, Hangzhou Normal University, Hangzhou, China.
  • Yongze Dong
    Nursing Department, Zhejiang Provincial People's Hospital, Hangzhou, China.
  • Huajuan Shen
    Nursing Department, Zhejiang Provincial People's Hospital, Hangzhou, China.
  • Junling Kang
    Department of Neurology, The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
  • Xiaodong Lu
    Department of Neurology, Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.
  • Guowei Jiang
    Department of Neurosurgery, Anhui No. 2 Provincial People's Hospital, Hefei, Anhui, China.
  • Lizzy M M Boots
    Department of Psychiatry and Neuropsychology and Alzheimer Center Limburg, School for Mental Health and Neuroscience (MHeNS), Maastricht University, Maastricht, Netherlands.
  • Heming Fu
    Department of Electrical and Computer Engineering, Stony Brook University, New York, USA.
  • Li Pan
  • Hongkai Chen
  • Zhenyu Yan
    Department of Electrical and Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China.
  • Guoliang Xing
    Department of Information Engineering, The Chinese University of Hong Kong, 999077, Hong Kong, China.
  • Shihua Cao
    School of Nursing, Hangzhou Normal University, Hangzhou, China.

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