Rheumatology

Latest AI and machine learning research in rheumatology for healthcare professionals.

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Exploring genetic and immune cell dynamics in systemic lupus erythematosus patients with Epstein-Barr virus infection via machine learning.

OBJECTIVES: EBV is a widespread virus implicated in various diseases, including SLE. However, the sp...

Exploring the Impact of PA and Sedentary Behavior on Gout Risk in Hyperuricemia: Insights From Machine Learning and SHAP Analysis.

BACKGROUND: Individuals with hyperuricemia (HUA) are widely recognized as being at increased risk fo...

[Machine learning models established to distinguish OA and RA based on immune factors in the knee joint fluid].

Objective Based on 25 indicators including immune factors, cell count classification, and smear resu...

Deep learning in the precise assessment of primary Sjögren's syndrome based on ultrasound images.

OBJECTIVES: This study aimed to investigate the value of a deep learning (DL) model based on greysca...

Facing the challenges of autoimmune pancreatitis diagnosis: The answer from artificial intelligence.

Current diagnosis of autoimmune pancreatitis (AIP) is challenging and often requires combining multi...

Data-Driven Strategies for Carbimazole Titration: Exploring Machine Learning Solutions in Hyperthyroidism Control.

BACKGROUND: University Hospitals Dorset (UHD) has more than 1000 thyroid patient contacts annually. ...

Deep learning enables automatic detection of joint damage progression in rheumatoid arthritis-model development and external validation.

OBJECTIVES: Although deep learning has demonstrated substantial potential in automatic quantificatio...

Discovery of New HER2 Inhibitors via Computational Docking, Pharmacophore Modeling, and Machine Learning.

The human epidermal growth factor receptor 2 (HER2) is a critical oncogene implicated in the develop...

Development and Validation of a Novel Model to Discriminate Idiosyncratic Drug-Induced Liver Injury and Autoimmune Hepatitis.

BACKGROUND AND AIM: Discriminating between idiosyncratic drug-induced liver injury (DILI) and autoim...

COX-2 Inhibitor Prediction With KNIME: A Codeless Automated Machine Learning-Based Virtual Screening Workflow.

Cyclooxygenase-2 (COX-2) is an enzyme that plays a crucial role in inflammation by converting arachi...

iMFP-LG: Identify Novel Multi-functional Peptides Using Protein Language Models and Graph-based Deep Learning.

Functional peptides are short amino acid fragments that have a wide range of beneficial functions fo...

Assessing the role of volumetric brain information in multiple sclerosis progression.

Multiple sclerosis is a chronic autoimmune disease that affects the central nervous system. Understa...

Clinical characteristics, prognosis, and predictive modeling in class IV ± V lupus nephritis.

OBJECTIVE: The objective of this study is to compare the clinical features and survival outcomes of ...

Personalized prediction of breast cancer candidates for Anti-HER2 therapy using F-FDG PET/CT parameters and machine learning: a dual-center study.

BACKGROUND: Accurately evaluating human epidermal growth factor receptor (HER2) expression status in...

Artificial intelligence and omics-based autoantibody profiling in dementia.

INTRODUCTION: Dementia is a neurodegenerative syndrome marked by the accumulation of disease-specifi...

Improved in Silico Identification of Protein-Protein Interactions Using Deep Learning Approach.

Protein-protein interactions (PPIs) perform significant functions in many biological activities like...

TNFR-LSTM: A Deep Intelligent Model for Identification of Tumour Necroses Factor Receptor (TNFR) Activity.

Tumour necrosis factors (TNFs) are key players in processes such as inflammation, cancer development...

Dissecting the Predictors of Cyber-Aggression Through an Explainable Machine Learning Model.

The general aggression model (GAM) suggests that cyber-aggression stems from individual characterist...

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