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

Foundations of AI (67) Artificial Intelligence (2365) Applications of AI (346)

Published on in Vol 3 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44185, first published .
Identifying Frailty in Older Adults Receiving Home Care Assessment Using Machine Learning: Longitudinal Observational Study on the Role of Classifier, Feature Selection, and Sample Size

Identifying Frailty in Older Adults Receiving Home Care Assessment Using Machine Learning: Longitudinal Observational Study on the Role of Classifier, Feature Selection, and Sample Size

Identifying Frailty in Older Adults Receiving Home Care Assessment Using Machine Learning: Longitudinal Observational Study on the Role of Classifier, Feature Selection, and Sample Size

Authors of this article:

Cheng Pan1 Author Orcid Image ;   Hao Luo2 Author Orcid Image ;   Gary Cheung3 Author Orcid Image ;   Huiquan Zhou2 Author Orcid Image ;   Reynold Cheng1 Author Orcid Image ;   Sarah Cullum3 Author Orcid Image ;   Chuan Wu1 Author Orcid Image
Article Authors Cited by (2) Tweetations (4) Metrics

Journals

  1. Kim T, Choi J, Ko M, Kim K. Development and Validation of a Machine Learning Method Using Vocal Biomarkers for Identifying Frailty in Community-Dwelling Older Adults: Cross-Sectional Study. JMIR Medical Informatics 2025;13:e57298 View
  2. Chan C. Using data and artificial intelligence to improve care pathways of older people experiencing falls and frailty: Opportunities, challenges and practical considerations for clinicians. Clinical Medicine 2026;26(2):100563 View