Conference item
Interpretable rheumatoid arthritis scoring via anatomy-aware multiple instance learning
- Abstract:
- The Sharp/van der Heijde (SvdH) score has been widely used in clinical trials to quantify radiographic damage in Rheumatoid Arthritis (RA), but its complexity has limited its adoption in routine clinical practice. To address the inefficiency of manual scoring, this work proposes a two-stage pipeline for interpretable image-level SvdH score prediction using dual-hand radiographs. Our approach extracts disease-relevant image regions and integrates them using attention-based multiple instance learning to generate image-level features for prediction. We propose two region extraction schemes: 1) sampling image tiles most likely to contain abnormalities, and 2) cropping patches containing disease-relevant joints. With Scheme 2, our best individual score prediction model achieved a Pearson’s correlation coefficient (PCC) of 0.943 and a root mean squared error (RMSE) of 15.73. Ensemble learning further boosted prediction accuracy, yielding a PCC of 0.945 and RMSE of 15.57, achieving state-of-the-art performance that is comparable to that of experienced radiologists (PCC = 0.97, RMSE = 18.75). Finally, our pipeline effectively identified and made decisions based on anatomical structures which clinicians consider relevant to RA progression.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
-
-
(Preview, Accepted manuscript, pdf, 14.9MB, Terms of use)
-
- Publisher copy:
- 10.1007/978-3-032-09569-5_6
Authors
+ Engineering and Physical Sciences Research Council
More from this funder
- Funder identifier:
- https://ror.org/0439y7842
- Grant:
- EP/S02428X/1
- Publisher:
- Springer
- Host title:
- Applications of Medical Artificial Intelligence: 4th International Workshop, AMAI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23, 2025, Proceedings
- Pages:
- 52-62
- Series:
- Lecture Notes in Computer Science
- Series number:
- 16206
- Place of publication:
- Cham, Switzerland
- Publication date:
- 2026-01-02
- Acceptance date:
- 2025-07-22
- Event title:
- 4th International Workshop, AMAI 2025, held in conjunction with MICCAI 2025
- Event location:
- Daejeon, South Korea
- Event website:
- https://sites.google.com/view/amai2025/home
- Event start date:
- 2025-09-23
- Event end date:
- 2025-09-23
- DOI:
- EISSN:
-
1611-3349
- ISSN:
-
0302-9743
- EISBN:
- 9783032095695
- ISBN:
- 9783032095688
- Language:
-
English
- Keywords:
- Pubs id:
-
2355879
- Local pid:
-
pubs:2355879
- Deposit date:
-
2026-02-11
- ARK identifier:
Terms of use
- Copyright holder:
- Bo et al.
- Copyright date:
- 2026
- Rights statement:
- © 2026 The Author(s), under exclusive license to Springer Nature Switzerland AG.
- Notes:
- The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford's Open Access Publications Policy, and a CC BY public copyright licence has been applied.
- Licence:
- CC Attribution (CC BY)
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