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

Frailty Detection, Assessment and Prediction (67) AI in Older Adult Care (42) Clinical Information and Decision Making (1957) Machine Learning (2131) Tools, Programs and Algorithms (387) mHealth for Screening (298)

Published on in Vol 8 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/62942, first published .
Machine Learning Models for Frailty Classification of Older Adults in Northern Thailand: Model Development and Validation Study

Machine Learning Models for Frailty Classification of Older Adults in Northern Thailand: Model Development and Validation Study

Machine Learning Models for Frailty Classification of Older Adults in Northern Thailand: Model Development and Validation Study

Authors of this article:

Natthanaphop Isaradech1, 2 Author Orcid Image ;   Wachiranun Sirikul1, 3, 4 Author Orcid Image ;   Nida Buawangpong5 Author Orcid Image ;   Penprapa Siviroj1 Author Orcid Image ;   Amornphat Kitro1, 2 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Yokokawa Y, Nakamura K, Sasaki T, Yokouchi S, Kimura F. Examination of Social Participation in Older Adults Undergoing Frailty Health Checkups Using Deep Learning Models. Geriatrics 2025;10(5):124 View
  2. Aldriwesh M, Alotibi R, Alqurainy N, Alrabiah S, Arafah A, Alghoribi M, Ajina R. The role of gut microbiome in aging-associated diseases: where do we stand now and how technology will transform the future. Gut Microbes 2026;18(1) View