This paper is in the following e-collection/theme issue:

Digital Health Reviews (1551) Machine Learning (1769) Decision Support for Health Professionals (1360) Artificial Intelligence (1773) mHealth for Screening (264) Falls Prevention in the Elderly (85) Development and Evaluation of Research Methods, Instruments and Tools (648) Methodological Innovations (30)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54934, first published .
The Applications of Artificial Intelligence for Assessing Fall Risk: Systematic Review

The Applications of Artificial Intelligence for Assessing Fall Risk: Systematic Review

The Applications of Artificial Intelligence for Assessing Fall Risk: Systematic Review

Authors of this article:

Ana González-Castro1 Author Orcid Image ;   Raquel Leirós-Rodríguez2 Author Orcid Image ;   Camino Prada-García3 Author Orcid Image ;   José Alberto Benítez-Andrades4 Author Orcid Image
Article Authors Cited by (9) Tweetations (3) Metrics

Journals

  1. Alsaleh H, Alsaad S, Alabdulwahab S, Vennu V, Bindawas S. Fall Prevention in Older Adults: Insights from Saudi Arabian Physical Therapists on the Otago Exercise Program. Risk Management and Healthcare Policy 2024;Volume 17:2689 View
  2. Le N, Sonka M, Skeete D, Romanowski K, Galet C. Predicting admission for fall‐related injuries in older adults using artificial intelligence: A proof‐of‐concept study. Geriatrics & Gerontology International 2025;25(2):232 View
  3. Yu X, Cai Y, Yang R, Ma F, Kim W. Revisiting sensor-based intelligent fall risk assessment for older people: A systematic review. Engineering Applications of Artificial Intelligence 2025;144:110176 View
  4. Turja T, Castaño-Rosa R. A scoping review: domestic fall risks in older adults stemming from unsafe behaviors and their association with physical environmental factors. Journal of Public Health 2025 View
  5. Bincalar A, Freeman C, schraefel m. Optimal Algorithms for Improving Pressure-Sensitive Mat Centre of Pressure Measurements. Sensors 2025;25(5):1283 View
  6. Gervasi C, Perego E, Galli F, Torri V, Castoldi M, Bombardieri E. Prevention of falls in hospitalized patients—evaluation of the effectiveness of a monitoring system (Verso Vision) developed with artificial intelligence. Frontiers in Digital Health 2025;7 View
  7. Gao Y, Zhang X, Zhao G, Shi Y, Zhang Y. BPSSL: Balanced pseudo-label based semi-supervised learning for medical image classification. Biomedical Signal Processing and Control 2025;109:108044 View
  8. Hao J. Artificial intelligence empowers physical therapy for neurological conditions. Neurological Sciences 2025 View

Conference Proceedings

  1. Zorriassatine F, Burton E, Boyd J, Naser A, Lotfi A. Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments. Cross-Species Insights: Drawing Lessons Between Bird Lameness Detection and Human Gait Anomaly Detection View