Rheumatology

Lupus

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

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Psychedelics, entactogens and psychoplastogens for depression and related disorders.

Currently, the most actively investigated rapidly acting antidepressants, anxiolytics and/or anti PT...

Discovery of Novel Anti-Acetylcholinesterase Peptides Using a Machine Learning and Molecular Docking Approach.

OBJECTIVE: Alzheimer's disease poses a significant threat to human health. Currenttherapeutic medici...

Deep learning enhanced deciphering of brain activity maps for discovery of therapeutics for brain disorders.

This study presents an artificial intelligence enhanced screening platform, DeepBAM, which enables ...

Identification of lipid metabolism-associated biomarkers in lupus nephritis by SVM model and therapeutic potential of Alisol B 23-acetate.

Systemic lupus erythematosus (SLE), a multifaceted autoimmune disorder, has lupus nephritis (LN) as ...

A high-throughput analysis of novel anti-fibrotics in human adult cardiac fibroblasts.

Myocardial fibrosis, a hallmark of heart failure (HF), contributes to disease progression and mortal...

Analysis of a nonsteroidal anti inflammatory drug solubility in green solvent via developing robust models based on machine learning technique.

This study develops and evaluates advanced hybrid machine learning models-ADA-ARD (AdaBoost on ARD R...

Tumor-specific draining lymph node CD8 T cells orchestrate an anti-tumor response to neoadjuvant PD-1 immune checkpoint blockade.

Elucidating the anti-tumor role of tumor-draining lymph nodes (tdLNs) in patients could offer critic...

Neuromethods: Basic Techniques for Evaluating the Nervous System in Nonclinical Studies.

The first session of the 2025 European Society of Toxicologic Pathology (ESTP) Congress reviewed rou...

Machine Learning-Driven QSAR Modeling of Anti-Cancer Activity from a Rationally Designed Synthetic Flavone Library.

Flavones, recognized as "privileged scaffolds" in drug discovery, hold significant promise as anti-c...

A machine learning model for predicting anatomical response to Anti-VEGF therapy in diabetic macular edema.

PURPOSE: To develop a machine learning model to predict anatomical response to anti-VEGF therapy in ...

Multifunctional Hydrogen-Bonded Organic Frameworks for Intelligent Anti-Counterfeiting and Food Safety Monitoring.

In an era of increasing digital threats and product counterfeiting, this study introduces MA-IPA@NPA...

Evaluating anti-VEGF responses in diabetic macular edema: A systematic review with AI-powered treatment insights.

Recent advances in deep learning and machine learning have greatly increased the capabilities of ext...

Neurostimulation for the Management of Epilepsy: Advances in Targeted Therapy.

BACKGROUND: Epilepsy is a multifaceted neurological disorder marked by seizures that can present wit...

ElixirSeeker: A Machine Learning Framework Utilizing Fusion Molecular Fingerprints for the Discovery of Lifespan-Extending Compounds.

Despite the growing interest in developing anti-aging drugs, high costs and low success rates of tra...

Brain metabolic imaging-based model identifies cognitive stability in prodromal Alzheimer's disease.

The recent approval of anti-amyloid pharmaceuticals for the treatment of Alzheimer's disease (AD) ha...

Aberrant formation of the neutrophil extracellular trap and the expression of the PLEKHA1 in systemic lupus erythematosus and ulcerative colitis.

Systemic lupus erythematosus (SLE) and ulcerative colitis (UC) are both chronic autoimmune diseases ...

Surfactant-Enhanced Anti-Swelling Hydrogel Flexible Sensor for Machine Learning-Assisted Underwater Gesture Recognition.

Hydrogels hold great promise as flexible sensors. However, the development of hydrogel sensors with ...

Anti- activity of clerodane diterpenes and their methyl ester derivatives from (Alismataceae).

The effect of the EtOAc extract of leaves against (trypomastigotes) was evaluated . As this extrac...

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