Arthritis

Recent advances in omics and the integration of multi-omics in osteoarthritis research.

Osteoarthritis (OA) is a complex disorder driven by the combination of environmental and genetic factors. Given its high global prevalence and heterogeneity, developing effective and personalized treatment methods is crucial. This requires identifying new disease mechanisms, drug targets, and biomarkers. Various omics approaches have been applied to identify OA-related genes, pathways, and biomark...

Digital health tools in juvenile idiopathic arthritis: a systematic literature review.

BACKGROUND: Nowadays, digital health technologies, including mobile apps, wearable technologies, social media, websites, electronic medical records, and artificial intelligence, are impacting disease management and outcomes. We aimed to analyse the characteristics and use of digital health tools in juvenile idiopathic arthritis (JIA).

Machine learning analysis of FOSL2 and RHoBTB1 as central immunological regulators in knee osteoarthritis synovium.

BackgroundKnee osteoarthritis is a debilitating disease with a complex pathogenesis. Synovitis, which refers to inflammation of the synovial membrane ...

Constructing machine learning-based risk prediction model for osteoarthritis in population aged 45 and above: NHANES 2011-2018.

Osteoarthritis is a widespread chronic joint disease, becoming increasingly prevalent, particularly among individuals over the age of 45. This conditi...

Feasibility of human ethomic biomarkers for the diagnosis and monitoring of hip osteoarthritis.

Radiographic imaging is typically used to diagnose osteoarthritis (OA). However, patients would typically be sent for imaging after they present to a ...

Can Artificial Intelligence Diagnose Knee Osteoarthritis?

This study analyzed the capability of GPT-4o to properly identify knee osteoarthritis and found that the model had good sensitivity but poor specifici...

Advancing osteoarthritis research: the role of AI in clinical, imaging and omics fields.

Osteoarthritis (OA) is a degenerative joint disease with significant clinical and societal impact. Traditional diagnostic methods, including subjectiv...

Accuracy of machine learning in identifying candidates for total knee arthroplasty (TKA) surgery: a systematic review and meta-analysis.

BACKGROUND: The application of machine learning (ML) in predicting the requirement for total knee arthroplasty (TKA) at knee osteoarthritis (KOA) pati...

Molecular features and diagnostic modeling of synovium- and IPFP-derived OA macrophages in the inflammatory microenvironment via scRNA-seq and machine learning.

BACKGROUND: Osteoarthritis (OA) is the leading cause of degenerative joint disease, with total joint replacement as the only definitive cure. However,...

Classification of Grades of Subchondral Sclerosis from Knee Radiographic Images Using Artificial Intelligence.

Osteoarthritis (OA) is the most common joint disease, affecting over 300 million people worldwide. Subchondral sclerosis is a key indicator of OA. Cur...

Assessing the Usability of ChatGPT Responses Compared to Other Online Information in Hand Surgery.

BACKGROUND: ChatGPT is a natural language processing tool with potential to increase accessibility of health information. This study aimed to: (1) ass...

Leveraging multi-modal feature learning for predictions of antibody viscosity.

The shift toward subcutaneous administration for biologic therapeutics has gained momentum due to its patient-friendly nature, convenience, reduced he...

The Role of Artificial Intelligence in the Diagnosis and Management of Rheumatoid Arthritis.

Artificial intelligence has emerged as a transformative tool in healthcare, offering capabilities such as early diagnosis, personalised treatment, an...

Predicting rheumatoid arthritis in the middle-aged and older population using patient-reported outcomes: insights from the SHARE cohort.

BACKGROUND: In light of global population aging and the increasing prevalence of Rheumatoid Arthritis (RA) with age, strategies are needed to address ...

Artificial intelligence to predict treatment response in rheumatoid arthritis and spondyloarthritis: a scoping review.

To analyse the types and applications of artificial intelligence (AI) technologies to predict treatment response in rheumatoid arthritis (RA) and spon...

Common genetic variants do not impact clinical prediction of methotrexate treatment outcomes in early rheumatoid arthritis.

BACKGROUND: Methotrexate (MTX) is the mainstay initial treatment of rheumatoid arthritis (RA), but individual response varies and remains difficult to...

Machine learning based association between inflammation indicators (NLR, PLR, NPAR, SII, SIRI, and AISI) and all-cause mortality in arthritis patients with hypertension: NHANES 1999-2018.

BACKGROUND: This study aimed to evaluate the relationship between CBC-derived inflammatory markers (NLR, PLR, NPAR, SII, SIRI, and AISI) and all-cause...

Ultrasound-based radiomics and machine learning for enhanced diagnosis of knee osteoarthritis: Evaluation of diagnostic accuracy, sensitivity, specificity, and predictive value.

PURPOSE: To evaluate the usefulness of radiomics features extracted from ultrasonographic images in diagnosing and predicting the severity of knee ost...

Identification of novel IL17-related genes as prognostic and therapeutic biomarkers of psoriasis using comprehensive bioinformatics analysis and machine learning.

Psoriasis is a common chronic skin disorder with a polygenic background. It is widely acknowledged that Th17/IL-17A axis plays a key role in the patho...

[Research progress of effect mechanism of acupotomy for knee osteoarthritis].

Acupotomy therapy demonstrates the definite clinical efficacy on knee osteoarthritis (KOA). After reviewing systematically the mechanism studies on ac...