ArticleDigital biomarkers
Dorsal Finger Fold Recognition by Convolutional Neural Networks for the Detection and Monitoring of Joint Swelling in Patients with Rheumatoid Arthritis.
Article in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 38 citations in OpenAlex.
- Digitally-supported patient-centered asynchronous outpatient follow-up in rheumatoid arthritis - an explorative qualitative study.BMC health services research · 2022Trial
- AI detects signs of inflammatory arthritis in hand images.Nature reviews. Rheumatology · 2026Article
- Structured prompting as reusable clinical tools.EULAR rheumatology open · 2026Article
- From pixels to prediction: improving imaging through AI in rheumatology.EULAR rheumatology open · 2026Review
- Clinical investigation of a digital biomarker for joint swelling in inflammatory arthritis based on automated quantification of dorsal finger fold patterns.Scientific reports · 2026Article
- A deep learning system for diagnosis of rheumatoid arthritis on digital hand photographs.BMC rheumatology · 2026Article
- Artificial Intelligence in Rheumatology: From Algorithms to Clinical Impact in Osteoporosis and Chronic Inflammatory Rheumatic Diseases.Journal of clinical medicine · 2026Article
- Preferences regarding technology to unobtrusively monitor symptoms in rheumatoid arthritis: a qualitative study using focus group discussions.Rheumatology international · 2025Article
- Patient self-assessment and virtual visit-based treatment decisions in rheumatoid arthritis: results from the multicentre Telemedicine in Rheumatoid Arthritis trial.EULAR rheumatology open · 2025Article
- Early detection of rheumatoid arthritis through patient empowerment by tailored digital monitoring and education: a feasibility study.Rheumatology international · 2025Article
- Integrating clinical features, inflammatory markers, and immune profiles: a Yunke-based nomogram model for rheumatoid arthritis prognosis.Frontiers in medicine · 2025Article
- Single-camera motion capture of finger joint mobility as a digital biomarker for disease activity in rheumatoid arthritis.Rheumatology advances in practice · 2025Article
- Evaluation of a hybrid telehealth care pathway for patients with axial spondyloarthritis including self-sampling at home: results of a longitudinal proof-of-concept mixed-methods study (TeleSpactive).Rheumatology international · 2024Article
- [Orthopedics and trauma surgery in the digital age].Orthopadie (Heidelberg, Germany) · 2024Review
- What does artificial intelligence mean in rheumatology?Archives of rheumatology · 2024Review
- Advancing Rheumatology Care Through Machine Learning.Pharmaceutical medicine · 2024Article
- Stepwise asynchronous telehealth assessment of patients with suspected axial spondyloarthritis: results from a pilot study.Rheumatology international · 2024Article
- Development of a deep learning model for automated detection of calcium pyrophosphate deposition in hand radiographs.Frontiers in medicine · 2024Article
- Recommendation to implementation of remote patient monitoring in rheumatology: lessons learned and barriers to take.RMD open · 2023Article
- Remote monitoring in rheumatology: seeing the right patient at the right time.Nature reviews. Rheumatology · 2023Article
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital biomarkers such as wearables are of increasing interest in monitoring rheumatic diseases, but they usually lack disease specificity. In this study, we apply convolutional neural networks (CNN) to real-world hand photographs in order to automatically detect, extract, and analyse dorsal finger fold lines as a correlate of proximal interphalangeal (PIP) joint swelling in patients with rheumatoid arthritis (RA). Hand photographs of RA patients were taken by a smartphone camera in a standardized manner. Overall, 190 PIP joints were categorized as either swollen or not swollen based on clinical judgement and ultrasound. Images were automatically preprocessed by cropping PIP joints and extracting dorsal finger folds. Subsequently, metrical analysis of dorsal finger folds was performed, and a CNN was trained to classify the dorsal finger lines into swollen versus non-swollen joints. Representative horizontal finger folds were also quantified in a subset of patients before and after resolution of PIP swelling and in patients with disease flares. In swollen joints, the number of automatically extracted deep skinfold imprints was significantly reduced compared to non-swollen joints (1.3, SD 0.8 vs. 3.3, SD 0.49,
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.