Arthritis

Artificial intelligence, machine learning and omic data integration in osteoarthritis.

OBJECTIVE: Artificial intelligence (AI), particularly its subfield of machine learning (ML), offer promising tools for integrating and interpreting high-dimensional omic data to advance our understanding of osteoarthritis (OA), a complex, multifactorial disease. The objective of this review is to summarize recent progress in applying ML approaches to single and integrative multi-omic data in OA an...

Can Patients Differentiate Responses by Orthopaedic Surgeons and ChatGPT Regarding Total Hip Arthroplasty?

INTRODUCTION: The digital age offers vast health information, boosting patient health literacy but also fostering challenges like misinformation. Large language models-driven chatbots such as chat generative pretrained transformer 3 (ChatGPT 3) blur human artificial intelligence (AI) content creation boundaries, potentially affecting healthcare literacy. This study aimed to assess perceived messag...

What can we learn about chronic rhinosinusitis through mucus?

PURPOSE OF REVIEW: Sinonasal mucus biomarkers have emerged as a powerful, noninvasive tool to better understand the immunopathology of chronic rhinosi...

Intelligent extraction of CT image landmarks for improving cam-type femoroacetabular impingement assessment.

OBJECTIVES: Femoroacetabular impingement (FAI) with cam-type morphology is a common hip disorder that can result in groin pain and eventually osteoart...

Localizing Knee Pain via Explainable Bayesian Generative Models and Counterfactual MRI: Data from the Osteoarthritis Initiative.

Osteoarthritis (OA) pain often does not correlate with magnetic resonance imaging (MRI)-detected structural abnormalities, limiting the clinical utili...

Do ChatGPT and Gemini's Recommendations Align With Established Guidelines for Hand and Upper Extremity Surgery?

BACKGROUND: The use of large language models (LLMs) such as ChatGPT and Gemini in clinical settings has surged, presenting potential benefits in reduc...

Deep-Learning System for Automatic Measurement of the Femorotibial Rotational Angle on Lower-Extremity Computed Tomography.

To develop and validate a deep-learning-based algorithm for automatic identification of anatomical landmarks and calculating femoral and tibial versio...

Effectiveness of artificial intelligence in classification of connective tissue diseases in patients with anti-nuclear antibody (ANA) positivity.

OBJECTIVES: The study aimed to investigate the classification performance of artificial intelligence (AI) in diagnosing connective tissue diseases(CTD...

Comparative Evaluation of Deep Learning and Foundation Model Embeddings for Osteoarthritis Feature Classification in Knee Radiographs.

Foundation models (FM) offer a promising alternative to supervised deep learning (DL) by enabling greater flexibility and generalizability without rel...

Deep learning for automated 3D assessment of rotator cuff muscle atrophy and fat infiltration prior to total shoulder arthroplasty.

BACKGROUND: Rotator cuff muscle pathology affects outcomes following total shoulder arthroplasty, yet current assessment methods lack reliability in q...

Artificial Intelligence for Knee Osteoarthritis Care and Rehabilitation: A Systematic Review.

OBJECTIVES: To explore how artificial intelligence (AI) can improve the clinical and rehabilitation management of knee osteoarthritis (KOA), emphasizi...

Advanced mass spectrometry techniques for monitoring biopharmaceutical host cell proteins.

Residual host cell proteins (HCPs) in biologic drug products can compromise safety or stability and must be carefully monitored. While traditional imm...

A Deep Learning Tool for Hip Minimum Joint Space Width Calculation on Antero-posterior Pelvis Radiographs.

BACKGROUND: Minimum joint space width (mJSW) is a useful quantitative metric of osteoarthritis progression in the hip, particularly as a continuous va...

A Scoping Review on AI-Supported Interventions for Non-Pharmacological Management of Chronic Rheumatic Diseases.

This review summarizes AI-supported non-pharmacological interventions for adults with chronic rheumatic diseases, detailing their components, purpose,...

Interpretive prediction of hyperuricemia and gout patients via machine learning analysis of human gut microbiome.

Hyperuricemia (HUA) and gout result from imbalances in uric acid metabolism and are closely associated with the gut microbiota. Advanced analytical me...

Machine learning using genotype and gene-expression data identifies alterations of genes involved in infection susceptibility, antigen presentation and cytokine signalling as key contributors to JIA risk prediction.

BACKGROUND: Previous genome-wide association studies (GWAS) have identified numerous genetic loci associated with juvenile idiopathic arthritis (JIA)....

UBE2D1 as a key biomarker in systemic juvenile idiopathic arthritis: a new perspective on diagnosis and disease activity assessment.

BACKGROUND: Early diagnosis is crucial for reducing disability and improving long-term prognosis in patients with systemic Juvenile Idiopathic Arthrit...

Confidence-Driven Deep Learning Framework for Early Detection of Knee Osteoarthritis.

Knee Osteoarthritis (KOA) is a prevalent musculoskeletal disorder that severely impacts mobility and quality of life, particularly among older adults....

Assessment of T2-weighted MRI-derived synthetic CT for the detection of suspected lumbar facet arthritis: a comparative analysis with conventional CT.

PURPOSE: We evaluated sCT generated from T2-weighted imaging (T2WI) using deep learning techniques to detect structural lesions in lumbar facet arthri...

Nuclear morphometrics coupled with machine learning identifies dynamic states of senescence across age.

Cellular senescence is an irreversible state of cell cycle arrest with a complex role in tissue repair, aging, and disease. However, inconsistencies i...