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

Formative Evaluation of Digital Health Interventions (3272) Registered Report (800) New Methods (1140) Clinical Information and Decision Making (1935) Artificial Intelligence (2162) Decision Support for Health Professionals (1555) Back Pain (137)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44187, first published .
Assessing Serious Spinal Pathology Using Bayesian Network Decision Support: Development and Validation Study

Assessing Serious Spinal Pathology Using Bayesian Network Decision Support: Development and Validation Study

Assessing Serious Spinal Pathology Using Bayesian Network Decision Support: Development and Validation Study

Authors of this article:

Adele Hill1 Author Orcid Image ;   Christopher H Joyner1 Author Orcid Image ;   Chloe Keith-Jopp2 Author Orcid Image ;   Barbaros Yet3 Author Orcid Image ;   Ceren Tuncer Sakar4 Author Orcid Image ;   William Marsh1 Author Orcid Image ;   Dylan Morrissey2, 5 Author Orcid Image
Article Authors Cited by (3) Tweetations (6) Metrics

Journals

  1. Yasinskaya A. Myofascial and spondylogeniccardialgia.Difficulties of diagnosis (a literature review with a clinical case study). Manual Therapy 2024;0(2):40 View
  2. Hill A, Morrissey D, Marsh W. “It’s the future, come on!”: a think aloud study exploring clinicians’ use of knowledge-based AI decision support. International Journal of Medical Informatics 2025;204:106089 View
  3. Pinto R, Kongsted A, Silva S, Hayden J, Downie A, Saragiotto B. Recent highlights in low back pain research, Part I: Diagnosis and Prognosis. Journal of Physiotherapy 2025 View