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Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64806, first published .
Doctors use futuristic tablet displaying holographic human anatomy for medical diagnosis.

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

Journals

  1. Bakr A, Basem Y, Sherif A, Ata A, Saad N, Fayed Y, Tamer M, Elkady M, Abdelmonem R. Tailored Therapeutic Strategies for Fetuses, Neonates, Pediatrics, Geriatrics, Athletes, and Critical Cases in the Era of Personalized Medicine. Diseases 2025;14(1):12 View
  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;27(7):828 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
  4. Ramanujam K, Carneiro S, Helal M, Ramanujam V. The effectiveness of artificial intelligence-based interventions on treatment outcomes for low back pain: A systematic review and meta-analysis of randomized controlled trials. Journal of Back and Musculoskeletal Rehabilitation 2026 View

Books/Policy Documents

  1. KANASE S, VAIDYA G. AI‐driven Innovations in Physiotherapy and Oncology 4. View

Conference Proceedings

  1. Naganjaneyulu S, Priyasri P, Jasmine Y, Prasad D. 2026 International Conference on Computing Theory and Wireless Communications (ICCTWC). Pain Prediction Analysis Using Physiological Signal and Deep Learning View