OBJECTIVE: Accurately predicting knee osteoarthritis (KOA) is essential for early detection and personalized treatment. We aimed to develop and test a magnetic resonance imaging (MRI)-based joint space (JS) radiomic model (RM) to predict radiographic...
Arthritis & rheumatology (Hoboken, N.J.)
Oct 26, 2022
Deep learning has emerged as the leading method in machine learning, spawning a rapidly growing field of academic research and commercial applications across medicine. Deep learning could have particular relevance to rheumatology if correctly utilize...
Arthritis & rheumatology (Hoboken, N.J.)
Oct 29, 2021
OBJECTIVE: To develop a bone shape measure that reflects the extent of cartilage loss and bone flattening in knee osteoarthritis (OA) and test it against estimates of disease severity.
Arthritis & rheumatology (Hoboken, N.J.)
Aug 6, 2021
OBJECTIVE: The relationship between in vivo knee load predictions and longitudinal cartilage changes has not been investigated. We undertook this study to develop an equation to predict the medial tibiofemoral contact force (MCF) peak during walking ...
Arthritis & rheumatology (Hoboken, N.J.)
Nov 10, 2020
OBJECTIVE: The pathophysiologic events that precede the onset of rheumatoid arthritis (RA) remain incompletely understood. This study was undertaken to identify changes in the serum proteome that precede the onset of RA, with the aim of providing new...
Arthritis & rheumatology (Hoboken, N.J.)
Nov 4, 2019
OBJECTIVE: Accurate prediction of treatment responses in rheumatoid arthritis (RA) patients can provide valuable information on effective drug selection. Anti-tumor necrosis factor (anti-TNF) drugs are an important second-line treatment after methotr...