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Automated Radiographic Total Sharp Score (ARTSS) in Rheumatoid Arthritis: A Solution to Reduce Inter-Intra Reader Variation and Enhancing Clinical Practice
Hajar Moradmand, Lei Ren
https://arxiv.org/abs/2509.06854

Automated Radiographic Total Sharp Score (ARTSS) in Rheumatoid Arthritis: A Solution to Reduce Inter-Intra Reader Variation and Enhancing Clinical Practice
Assessing the severity of rheumatoid arthritis (RA) using the Total Sharp/Van Der Heijde Score (TSS) is crucial, but manual scoring is often time-consuming and subjective. This study introduces an Automated Radiographic Sharp Scoring (ARTSS) framework that leverages deep learning to analyze full-hand X-ray images, aiming to reduce inter- and intra-observer variability. The research uniquely accommodates patients with joint disappearance and variable-length image sequences. We developed ARTSS us…

RAM-W600: A Multi-Task Wrist Dataset and Benchmark for Rheumatoid Arthritis
Songxiao Yang, Haolin Wang, Yao Fu, Ye Tian, Tamotsu Kamishima, Masayuki Ikebe, Yafei Ou, Masatoshi Okutomi
https://arxiv.org/abs/2507.05193

RAM-W600: A Multi-Task Wrist Dataset and Benchmark for Rheumatoid Arthritis
Rheumatoid arthritis (RA) is a common autoimmune disease that has been the focus of research in computer-aided diagnosis (CAD) and disease monitoring. In clinical settings, conventional radiography (CR) is widely used for the screening and evaluation of RA due to its low cost and accessibility. The wrist is a critical region for the diagnosis of RA. However, CAD research in this area remains limited, primarily due to the challenges in acquiring high-quality instance-level annotations. (i) The w…

Network Community Detection and Novelty Scoring Reveal Underexplored Hub Genes in Rheumatoid Arthritis
Neda Amirirad, Hiroki Sayama
https://arxiv.org/abs/2509.00897 https://

Network Community Detection and Novelty Scoring Reveal Underexplored Hub Genes in Rheumatoid Arthritis
Understanding the modular structure and central elements of complex biological networks is critical for uncovering system-level mechanisms in disease. Here, we constructed weighted gene co-expression networks from bulk RNA-seq data of rheumatoid arthritis (RA) synovial tissue, using pairwise correlation and a percolation-guided thresholding strategy. Community detection with Louvain and Leiden algorithms revealed robust modules, and node-strength ranking identified the top 50 hub genes globally…

Scientists revive ancient gene to target #gout and fatty #liver disease. https://phys.org/news/2025-08-scientis

Scientists revive ancient gene to target gout and fatty liver disease
Gout, a form of arthritis caused by crystals that build up in joints and cause swelling and pain, is one of humanity's oldest diseases. Scientists at Georgia State University may have found an ancient solution to treat it.