Rheumatology

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

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Evaluating large language models as a supplementary patient information resource on antimalarial use in systemic lupus erythematosus.

ObjectiveTo assess the accuracy, completeness, and reproducibility of Large Language Models (LLMs) (...

Review of 2024 publications on the applications of artificial intelligence in rheumatology.

The integration of artificial intelligence (AI) into rheumatology has revolutionized research and cl...

Comparative analysis of machine learning and deep learning algorithms for knee arthritis detection using YOLOv8 models.

Knee arthritis is a prevalent joint condition that affects many people worldwide. Early detection an...

Development and validation of a machine learning approach for screening new leprosy cases based on the leprosy suspicion questionnaire.

Leprosy is a dermatoneurological disease and can cause irreversible nerve damage. In addition to bei...

DeepTree-AAPred: Binary tree-based deep learning model for anti-angiogenic peptides prediction.

Anti-angiogenic peptides (AAPs) show important potential in tumor therapy by limiting the growth and...

Disease diagnostics using machine learning of B cell and T cell receptor sequences.

Clinical diagnosis typically incorporates physical examination, patient history, various laboratory ...

Plasma Cytokine and Chemokine Profiles Predict Efficacy and Toxicity of Anti-CD19 CAR-T Cell Therapy in Large B-Cell Lymphoma.

BACKGROUND: Anti-CD19 chimeric antigen receptor T-cell (CAR-T) therapy has emerged as a promising tr...

Use of a Convolutional Neural Network to Predict the Response of Diabetic Macular Edema to Intravitreal Anti-VEGF Treatment: A Pilot Study.

PURPOSE: To utilize a convolutional neural network (CNN) to predict the response of treatment-naïve ...

Artificial intelligence versus neurologists: A comparative study on multiple sclerosis expertise.

INTRODUCTION: Multiple sclerosis (MS) is an autoimmune neurodegenerative disease affecting the centr...

RAG_MCNNIL6: A Retrieval-Augmented Multi-Window Convolutional Network for Accurate Prediction of IL-6 Inducing Epitopes.

Interleukin-6 (IL-6) is a critical cytokine involved in immune regulation, inflammation, and the pat...

Prediction of mortality risk in critically ill patients with systemic lupus erythematosus: a machine learning approach using the MIMIC-IV database.

OBJECTIVE: Early prediction of long-term outcomes in patients with systemic lupus erythematosus (SLE...

Machine learning for the early prediction of long-term cognitive outcome in autoimmune encephalitis.

BACKGROUND AND OBJECTIVE: Autoimmune encephalitis (AE) is an immune-mediated disease. Some patients ...

Automatic Joint Lesion Detection by enhancing local feature interaction.

Recently, deep learning models have demonstrated impressive performance in Automatic Joint Lesion De...

Deep learning-based prediction of autoimmune diseases.

Autoimmune Diseases are a complex group of diseases caused by the immune system mistakenly attacking...

Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence.

Artificial intelligence (AI) has emerged as a transformative force in precision medicine, revolution...

Application of deep learning algorithm for judicious use of anti-VEGF in diabetic macular edema.

Diabetic Macular Edema (DME) is a major complication of diabetic retinopathy characterized by fluid ...

Discovery of TRPV4-Targeting Small Molecules with Anti-Influenza Effects Through Machine Learning and Experimental Validation.

Transient receptor potential vanilloid 4 (TRPV4) is a calcium-permeable cation channel critical for ...

Developing an interpretable machine learning model for diagnosing gout using clinical and ultrasound features.

OBJECTIVE: To develop a machine learning (ML) model using clinical data and ultrasound features for ...

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