Rheumatology

Lupus

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

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Enhancing Functional Protein Design Using Heuristic Optimization and Deep Learning for Anti-Inflammatory and Gene Therapy Applications.

Protein sequence design is a highly challenging task, aimed at discovering new proteins that are mor...

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 ...

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...

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 ...

Identification and validation of key autophagy-related genes in lupus nephritis by bioinformatics and machine learning.

INTRODUCTION: Lupus nephritis (LN) is one of the most frequent and serious organic manifestations of...

Ultrasensitive Detection of Circulating Plasma Cells Using Surface-Enhanced Raman Spectroscopy and Machine Learning for Multiple Myeloma Monitoring.

Multiple myeloma is a hematologic malignancy characterized by the proliferation of abnormal plasma c...

Using artificial intelligence to optimize anti-seizure treatment and EEG-guided decisions in severe brain injury.

Electroencephalography (EEG) is invaluable in the management of acute neurological emergencies. Char...

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the...

Identification of dequalinium as a potent inhibitor of human organic cation transporter 2 by machine learning based QSAR model.

Human organic cation transporter 2 (hOCT2/SLC22A2) is a key drug transporter that facilitates the tr...

Therapeutic potential of against monkeypox: antioxidant, anti-inflammatory, and computational insights.

BACKGROUND: Monkeypox (Mpox) is a re-emerging zoonotic disease with limited therapeutic options, nec...

Treatment of neovascular age-related macular degeneration: one year real-life results with intravitreal Brolucizumab.

BACKGROUND: Age-related macular degeneration (AMD) is a prevalent cause of irreversible vision loss ...

Risk Prediction of Liver Injury in Pediatric Tuberculosis Treatment: Development of an Automated Machine Learning Model.

PURPOSE: Drug-induced liver injury (DILI) is one of the most common and serious adverse drug reactio...

A python approach for prediction of physicochemical properties of anti-arrhythmia drugs using topological descriptors.

In recent years, machine learning has gained substantial attention for its ability to predict comple...

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