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Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71560, first published .
Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait

Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait

Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait

Journals

  1. Wang S, Wang L, Cheng H, Li H, Zhang Q, He C, Fu C, Wei Q. Targeting autophagy in doxorubicin-induced cardiotoxicity: A comprehensive review of scientific landscapes and therapeutic innovations. Ageing Research Reviews 2025;110:102818 View
  2. Hu T, Xi J, Xie N, Zhang X, Huang N, Cheng Y. Multi-omics analysis reveals the protective role of transcriptional enhancer factor and the pathogenic mechanism of monocytes in Parkinson's disease. Brain Research Bulletin 2025;232:111594 View
  3. Liu R, Zhang S, Xiao Y, Cheng Y, Shang H. The Effects of Digital Health Interventions on Motor Symptoms, Nonmotor Symptoms, and Quality of Life in Patients With Parkinson Disease: Systematic Review and Meta-Analysis of Randomized Controlled Trials. Journal of Medical Internet Research 2026;28:e79935 View
  4. Jin J, Jiang Y, Zhou Y, Zhu W, Hua J, Cheng W, Shi Y, Pan L. AI-Enabled Flexible Sensing Ecosystems for Parkinson’s Disease: Advancing Digital Biomarkers and Closed-Loop Interventions. Sensors 2026;26(7):2071 View