Rheumatology

Beyond human gold standards: A multimodel framework for automated abstract classification and information extraction.

Meta-research and evidence synthesis require considerable resources. Large language models (LLMs) have emerged as promising tools to assist in these processes, yet their performance varies across models, limiting their reliability. Taking advantage of the large availability of small size (<10 billion parameters) open-source LLMs, we implemented an agreement-based framework in which a decision is t...

Ligand-based prediction of anti-bacterial compounds: Overcoming class imbalance in molecular data.

In the emergence of pan-drug-resistant bacteria, there is an urgent demand for the discovery of structurally novel antibiotics. While traditional drug development and screening procedures are cumbersome, machine learning models (ML) have shown potential to predict anti-bacterial properties of chemical compounds and shortening the screening process immensely. However, the performance of existing ML...

Iterative learning for joint image denoising and motion artifact correction of 3D brain MRI.

Image noise and motion artifacts greatly affect the quality of brain magnetic resonance imaging (MRI) and negatively influence downstream medical imag...

Evaluating the performance of Large language models in rheumatology for connective tissue Diseases: DeepSeek-R1, ChatGPT-4.0, Copilot, and Gemini-2.0.

BACKGROUND: Large language models (LLMs) demonstrate significant potential in medical information provision and may serve as valuable tools for patien...

Simulation-guided optimization of one-step gold nanoparticle amplification for paper-based detection of anti-IFN-γ autoantibodies.

Adult-onset immunodeficiency (AOID) caused by anti-interferon-γ autoantibodies (anti-IFN-γ Abs) lacks rapid, sensitive diagnostic tools suitable for f...

An Ultrasound-Based Machine Learning Model for Differentiating IgG4-Related Sialadenitis and Primary Sjögren's Syndrome.

INTRODUCTION AND AIMS: To establish and validate an interpretable machine learning (ML) model based on ultrasound (US) scoring system for differentiat...

Artificial Intelligence and Machine Learning for Osteoarthritis and Cartilage Assessment.

Osteoarthritis (OA) affects over 500 million people globally and poses diagnostic and management challenges due to its complex pathophysiology. Artifi...

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. Larg...

Artificial intelligence in age-related macular degeneration: Advancing diagnosis, prognosis, and treatment.

Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss in older adults. While anti-vascular endothelial growth factor (...

Nivolumab plus ipilimumab for potentially resectable hepatocellular carcinoma: Long-term efficacy and biomarker exploration.

BACKGROUND & AIMS: Immune checkpoint inhibitor-based combination therapy has demonstrated high objective response rates in patients with hepatocellula...

Elucidating anti-triple-negative breast cancer mechanisms and mitigating toxicity of Fritillaria thunbergii Miq.: A multi-omics and network pharmacology approach.

ETHNOPHARMACOLOGICAL RELEVANCE: Fritillaria thunbergii Miq. (Zhebeimu, ZBM) is traditionally recognized in Chinese medicine for its effects of clearin...

Deep learning-based quantitative assessment of renal chronicity indices in lupus nephritis.

Renal chronicity indices (CI) have been identified as strong predictors of long-term outcomes in lupus nephritis (LN) patients. However, assessment by...

Systemic Lupus Erythematosus prediction using Epistatic-Quantile Fusion Transformer network with integrated multi-omics and clinical data.

Systemic Lupus Erythematosus (SLE) is a complex autoimmune disorder with heterogeneous symptoms and overlapping clinical presentations, making early p...

Artificial intelligence in radiology examinations: a psychometric comparison of question generation methods.

PURPOSE: This study aimed to evaluate the usability of artificial intelligence (AI)-based question generation methods-Chat Generative Pre-trained Tran...

Emerging innovations in ophthalmic drug delivery for diabetic retinopathy: a translational perspective.

Diabetic retinopathy (DR) is a progressive microvascular complication of diabetes and a leading cause of vision impairment worldwide. Despite advancem...

PediMS: A Pediatric Multiple Sclerosis Lesion Segmentation Dataset.

Multiple Sclerosis (MS) is a chronic autoimmune disease that primarily affects the central nervous system and is predominantly diagnosed in adults, ma...

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...

Deep learning for giant cell arteritis diagnosis on temporal artery biopsy.

OBJECTIVES: Giant Cell Arteritis (GCA) is a vasculitis affecting large and medium-caliber arteries, requiring early and accurate diagnosis to prevent ...