AIMC Topic: Arthritis, Rheumatoid

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Sex bias consideration in healthcare machine-learning research: a systematic review in rheumatoid arthritis.

BMJ open
OBJECTIVE: To assess the acknowledgement and mitigation of sex bias within studies using supervised machine learning (ML) for improving clinical outcomes in rheumatoid arthritis (RA).

Leveraging machine learning for drug repurposing in rheumatoid arthritis.

Drug discovery today
Rheumatoid arthritis (RA) presents a significant challenge in clinical management because of the dearth of effective drugs despite advances in understanding its mechanisms. Drug repurposing has emerged as a promising strategy to address this gap, off...

Hybrid attention-CNN model for classification of gait abnormalities using EMG scalogram images.

Journal of medical engineering & technology
This research aimed to develop an algorithm for classifying scalogram images generated from electromyography data of patients with Rheumatoid Arthritis and Prolapsed Intervertebral Disc. Electromyography is valuable for assessing muscle function and ...

Targeted nanoliposomes for precision rheumatoid arthritis therapy: a review on mechanisms and potential.

Drug delivery
Rheumatoid arthritis (RA) is an inflammatory immune-triggered disease that causes synovitis, cartilage degradation, and joint injury. In nanotechnology, conventional liposomes were extensively investigated for RA. However, they frequently undergo rap...

Predicting abatacept retention using machine learning.

Arthritis research & therapy
BACKGROUND: The incorporation of machine learning is becoming more prevalent in the clinical setting. By predicting clinical outcomes, machine learning can provide clinicians with a valuable tool for refining precision medicine approaches and improvi...

Multistage deep learning methods for automating radiographic sharp score prediction in rheumatoid arthritis.

Scientific reports
The Sharp-van der Heijde score (SvH) is crucial for assessing joint damage in rheumatoid arthritis (RA) through radiographic images. However, manual scoring is time-consuming and subject to variability. This study proposes a multistage deep learning ...

Association of and gene polymorphisms and ERAP2 protein with the susceptibility and severity of rheumatoid arthritis in the Ukrainian population.

Frontiers in immunology
INTRODUCTION: Rheumatoid arthritis (RA) is a long-term autoimmune disorder that primarily affects joints. Although RA is chiefly associated with HLA class II, nevertheless some HLA class I associations have also been observed. These molecules present...

Machine learning-based prediction model integrating ultrasound scores and clinical features for the progression to rheumatoid arthritis in patients with undifferentiated arthritis.

Clinical rheumatology
OBJECTIVES: Predicting rheumatoid arthritis (RA) progression in undifferentiated arthritis (UA) patients remains a challenge. Traditional approaches combining clinical assessments and ultrasonography (US) often lack accuracy due to the complex intera...

Deciphering hub genes and immune landscapes related to neutrophil extracellular traps in rheumatoid arthritis: insights from integrated bioinformatics analyses and experiments.

Frontiers in immunology
BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by synovial inflammation and progressive joint destruction. Neutrophil extracellular traps (NETs), a microreticular structure formed after neutrophil death, have rece...

Metabolic reprogramming and macrophage expansion define ACPA-negative rheumatoid arthritis: insights from single-cell RNA sequencing.

Frontiers in immunology
BACKGROUND: Anti-citrullinated peptide antibodies (ACPA)-negative (ACPA-) rheumatoid arthritis (RA) presents significant diagnostic and therapeutic challenges due to the absence of specific biomarkers, underscoring the need to elucidate its distincti...