Latest AI and machine learning research in rheumatology for healthcare professionals.
BACKGROUND: Realizing the full potential of human genetics requires identifying causal variants and genes underlying association signals. Molecular quantitative trait locus (molQTL) analyses, such as expression QTL (eQTL) and splicing QTL (sQTL), link genetic variants to intermediate molecular phenotypes, but pinpointing causal variants and their regulatory effects remains challenging. Here, we in...
This review highlights the problem of protein molecule aggregation, which represents a significant challenge in the field of biopharmaceuticals. Protein aggregation is critical because it can affect the efficacy and safety of biopharmaceuticals, including those used to treat autoimmune diseases and various cancers. From a regulatory perspective, protein aggregation is recognized as a critical qual...
Pachymic acid (PA) is a natural active component of Poria cocos(Schw.)Wol. Although PA exhibits antitumor activity in multiple cancers, its effects an...
Paratuberculosis, caused by Mycobacterium avium subsp. paratuberculosis (MAP), is a chronic, incurable enteritis of ruminants in which late-onset clin...
It is important to enhance the overall efficacy of artificial joint systems by addressing friction and oxidation issues at the joint prosthesis interf...
BACKGROUND: Hashimoto's thyroiditis (HT) is the most common autoimmune thyroid disorder, often diagnosed using ultrasound. However, conventional gray-...
OBJECTIVES: Severe infections are a primary cause of morbidity and premature mortality in patients with Systemic Lupus Erythematosus (SLE). Although S...
BACKGROUND: Fever of unknown origin (FUO) remains diagnostically challenging because of heterogeneous causes, non-specific clinical manifestations, an...
INTRODUCTION: Gout typically develops from hyperuricemia (HUA), but the metabolic alterations driving this transition remain poorly understood, limiti...
Cyclin-dependent kinases (CDKs), traditionally recognized for their pivotal role in cell cycle control, have emerged as versatile regulators orchestra...
OBJECTIVE: This study aimed to develop a robust transcriptomic diagnostic signature for Sjögren's disease (SjD; formerly Sjögren's syndrome) and eluci...
BACKGROUND: Systematic reviews are essential for evidence-based practice but remain resource-intensive, particularly during full-text data extraction ...
BACKGROUND: Recent advances in artificial intelligence (AI) have redefined shoulder arthroplasty, ultimately improving diagnostic accuracy, refining s...
OBJECTIVE: Given the challenges in predicting systemic lupus erythematosus (SLE) disease activity and the limitations of existing assessment tools, th...
PURPOSE: To identify which features best differentiate Sjögren's-related from non-Sjögren's related dry eye disease (DED) using machine-learning model...
Triple-negative breast cancer (TNBC) is classified as an immunologically cold tumor, which markedly weakens the therapeutic efficacy of immune checkpo...
OBJECTIVES: To develop a robust and interpretable machine learning framework for arthritis risk prediction and to identify important risk factors asso...
Large language models (LLMs) with multimodal capabilities may support automated assessment of cutaneous disease activity in dermatomyositis (DM). We e...
BACKGROUND: A major challenge facing prostate cancer (PCa) cells is oxidative stress, yet the precise role and underlying mechanisms remain inadequate...
BACKGROUND: Systemic lupus erythematosus (SLE) is a complex autoimmune disease, making accurate diagnosis and effective treatment challenging. Despite...