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

Machine Learning (2260) Tools, Programs and Algorithms (416) Decision Support for Health Professionals (1659) Advanced Data Analytics in eHealth (240) Clinical Communication, Electronic Consultation and Telehealth (813) Internet for Rehabilitation (97) Cognitive and Neurorehabilitation (382) Internet of Things (102) mHealth for Rehabilitation (392) New Technologies (120) Back Pain (147) Artificial Intelligence (2397)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64806, first published .
Predicting Pain Response to a Remote Musculoskeletal Care Program for Low Back Pain Management: Development of a Prediction Tool

Predicting Pain Response to a Remote Musculoskeletal Care Program for Low Back Pain Management: Development of a Prediction Tool

Predicting Pain Response to a Remote Musculoskeletal Care Program for Low Back Pain Management: Development of a Prediction Tool

Authors of this article:

Anabela C Areias1 Author Orcid Image ;   Robert G Moulder2 Author Orcid Image ;   Maria Molinos1 Author Orcid Image ;   Dora Janela1 Author Orcid Image ;   Virgílio Bento1 Author Orcid Image ;   Carolina Moreira1, 3 Author Orcid Image ;   Vijay Yanamadala1, 4, 5 Author Orcid Image ;   Steven P Cohen6, 7, 8, 9, 10, 11 Author Orcid Image ;   Fernando Dias Correia1, 12 Author Orcid Image ;   Fabíola Costa1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

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  2. Janela D, Tong X, Pires D, Fonseca H, Costa F. Predicting pain outcomes after digital care in chronic spinal pain: the roles of disability, work impairment, and occupation in a secondary analysis of a prospective clinical study. Pain Medicine 2026 View
  3. Tse M, He J, Kwok T. A Gamified Pain Management Intervention for Adults With Chronic Pain in Mainland China: Single-Arm Pre-Post Pilot Study With Machine Learning Predictive Modeling. JMIR Formative Research 2026;10:e78823 View