Accessibility settings

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

Imaging Informatics (348) Decision Support for Health Professionals (1677) Machine Learning (2289) Immunology, Allergy, Rheumatology (159) Digital Biomarkers and Digital Phenotyping (338) Precision Medicine (194) Digital Pain Assessment and Management (266)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/78338, first published .
Nomograms Based on X-Ray Radiomics for Predicting Pain Progression in Knee Osteoarthritis Using Data From the Foundation for the National Institutes of Health: Development and Validation Study

Nomograms Based on X-Ray Radiomics for Predicting Pain Progression in Knee Osteoarthritis Using Data From the Foundation for the National Institutes of Health: Development and Validation Study

Nomograms Based on X-Ray Radiomics for Predicting Pain Progression in Knee Osteoarthritis Using Data From the Foundation for the National Institutes of Health: Development and Validation Study

Authors of this article:

Yingwei Sun1 Author Orcid Image ;   Jing Liu2 Author Orcid Image ;   Chunbo Deng3 Author Orcid Image ;   Chengbao Peng2 Author Orcid Image ;   Shinong Pan4 Author Orcid Image ;   Xueyong Liu5 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Piotr Tryczyński , Jakub Wrona , Jakub Sałak , Piotr Helbin , Aleksandra Gralec , Sebastian Ożga , Wiktoria Donocik , Aleksandra Spirkowicz . ARTIFICIAL INTELLIGENCE IN THE EARLY DETECTION AND PROGRESSION PREDICTION OF OSTEOARTHRITIS: A NARRATIVE REVIEW OF CURRENT TECHNOLOGIES AND CLINICAL IMPLICATIONS. International Journal of Innovative Technologies in Social Science 2026;3(1(49)) View