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Localizing Knee Pain via Explainable Bayesian Generative Models and Counterfactual MRI: Data from the Osteoarthritis Initiative

Crossref DOI link: https://doi.org/10.1007/s10278-025-01678-1

Published Online: 2025-09-24

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Chuang, Tzu-Yi

Lian, Pin-Hsun

Kuo, Yu-Chen

Chang, Gary Han https://orcid.org/0000-0002-7732-800X
Funding

Funding for this research was provided by:

National Science and Technology Council (project numbers 113-2311-B-002 -012 -)
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Text and Data Mining valid from 2025-09-24

Version of Record valid from 2025-09-24
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Article History

Received: 20 June 2025

Revised: 18 August 2025

Accepted: 2 September 2025

First Online: 24 September 2025

Declarations

:

: This study represents a secondary analysis of publicly available, de-identified data from the Osteoarthritis Initiative (OAI) database and was deemed exempt from review by the National Taiwan University Hospital Research Ethics Committee (NTUH-REC No. 202205031W).The original OAI study protocol, amendments, and informed consent documentation were reviewed and approved by the institutional review boards at all participating clinical centers. Written informed consent was obtained from all 4796 OAI participants prior to each clinical visit during the original data collection period (2004–2015).

: This study utilized publicly available, de-identified data from the OAI database. Informed consent for the original data collection was obtained by the OAI investigators from all participants during the original study.

: This study involved analysis of publicly available, de-identified datasets. No individual participant data that could lead to identification is presented in this manuscript.

: The authors declare no competing interests.

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