Arthritis

Generative artificial intelligence in osteoarthritis: A systematic scoping review of current applications and future directions.

OBJECTIVE: Generative artificial intelligence (GenAI) is a transformative tool capable of producing realistic synthetic data, modeling complex data, and translating large volumes of information into clinically meaningful insights. This systematic scoping review aimed to characterize the current applications of GenAI in OA care and research. DESIGN: Medline, EMBASE, Pubmed and Scopus were searched ...

AI-powered biomechanical modeling for ACL-reconstructed knees: predicting knee joint contact forces via computer vision and deep learning.

BACKGROUND: Patients undergoing anterior cruciate ligament reconstruction (ACLR) are at high risk of osteoarthritis or secondary injuries, with abnormal knee contact forces (KCFs) identified as a key factor in joint degeneration. Traditional KCF assessment relies on expensive lab systems while advances in computer vision and AI now enable low-cost alternatives. However, currently available methods...

Which matters more for preventing knee replacements: reducing overactivity or combating inactivity?

BACKGROUND: Daily physical activity (PA) has been gaining attention for the management and prevention of knee osteoarthritis (OA). AIMS: This study ai...

The Emory Knee Radiograph (MRKR) Dataset.

The Emory Knee Radiograph (MRKR) dataset is a large, demographically diverse collection of 503,261 knee radiographs from 83,011 patients, 40% of which...

Machine learning-based prediction model for fall risk among individuals with arthritis in China: an analysis using the China Health and Retirement Longitudinal Study (CHARLS) database.

BACKGROUND: Falling has become a global public health problem. Individuals with arthritis have a higher risk of falling because of joint pain, poor mu...

Bridging Population Patterns and Individual Prediction: Framework for Prospective Multimorbidity Study.

BACKGROUND: Multimorbidity has become a major global public health challenge. However, existing research primarily emphasizes the identification of di...

Knee osteoarthritis classification using Optimized Granger Causality Inspired Graph Neural Network with Accelerated Model-agnostic Explanations.

BACKGROUND: Knee osteoarthritis (KOA) is a common, degenerative joint condition where cartilage wears away, causing bone-on-bone friction, leading to ...

Dysbiosis of fecal virome in pediatric Crohn's disease and its dynamic changes during infliximab therapy.

UNLABELLED: The gut virome is an emerging but underexplored component of the human microbiota, especially in pediatric Crohn's disease (CD). This stud...

Global patterns and predictors of initial treatment in early rheumatoid arthritis: insights from a multinational machine learning study.

BACKGROUND: Rheumatoid arthritis (RA) treatment guidelines recommend early initiation of disease-modifying antirheumatic drugs (DMARDs), but actual pr...

Integrating machine learning with SHAP to uncover multi-tissue molecular signatures in Osteoarthritis progression.

Osteoarthritis (OA) is a chronic joint disorder characterized by pain, reduced mobility, and structural degeneration. Despite its complex etiology and...

IMMT downregulation promotes osteoarthritis development by inducing mitochondrial dysfunction.

OBJECTIVE: This study aimed to identify key mitochondria-related genes involved in the pathogenesis of osteoarthritis (OA). METHODS: Publicly availabl...

The feasibility of using deep learning technologies to preliminarily identify patients with advanced knee osteoarthritis via smartphone videos.

Do ChatGPT and Gemini provide accurate answers to patient questions about glenohumeral arthritis?

BACKGROUND: Machine learning, a subset of artificial intelligence, enables large language models (LLMs) like ChatGPT and Gemini to analyze data, learn...

Machine learning-based multiclass model for autoimmune disease diagnosis and classification through nailfold videocapillaroscopy features.

OBJECTIVE: To develop and validate a predictive model for distinguishing controls (Ctr), rheumatoid arthritis (RA) and systemic lupus erythematosus (S...

Development and validation of a deep learning markerless system for lower-limb kinematics in hip and knee osteoarthritis population.

With the advancement of deep learning technology, markerless systems have emerged as a cost-effective and user-friendly alternative to marker-based sy...

Advances in Gait Alterations and Rehabilitation After Anterior Cruciate Ligament Reconstruction: Biomechanics and Emerging Technologies.

Anterior cruciate ligament (ACL) injuries are prevalent in sports and daily life, often leading to functional instability and long-term complications ...

Low-input deep learning platform for citrullinated peptide identification, autoantigen discovery and rheumatoid arthritis treatment stratification.

Post-translationally modified proteins are crucial autoantigens in autoimmune diseases, with citrullinated proteins being key targets of autoantibodie...

Enhanced Magnetic Resonance Imaging-Based Knee Cartilage Segmentation Using a Swin-UNet Conditional Generative Adversarial Network: Development and Validation Study.

BACKGROUND: Accurate segmentation of cartilage from magnetic resonance imaging (MRI) is crucial for the diagnosis and surgical planning of knee osteoa...

Developing a Metabolic-Associated Prognostic Index for Risk Stratification and Therapeutic Guidance in Stage I Lung Adenocarcinoma via Multiomics Analysis.

PURPOSE: Early-stage lung adenocarcinoma (LUAD) exhibits substantial clinical heterogeneity that is not fully explained by TNM staging, highlighting t...

Predicting early discontinuation of adalimumab in patients with rheumatoid arthritis using machine learning: A specialty pharmacy-based approach.

BACKGROUND: Patients with rheumatoid arthritis (RA) prescribed adalimumab often discontinue treatment within 6 months because of a perceived lack of b...