Rheumatology

Lupus

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

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AAGP integrates physicochemical and compositional features for machine learning-based prediction of anti-aging peptides.

Aging is a natural phenomenon characterized by the loss of normal morphology and physiological funct...

Redesigning miR-34a: structural and chemical advances in the therapeutic development of an miRNA anti-cancer agent.

MicroRNAs (miRNAs) represent a promising class of therapeutics due to their ability to down-regulate...

Unraveling Liver Cirrhosis: Bridging Pathophysiology to Innovative Therapeutics.

Liver cirrhosis is a complex and progressive condition resulting from sustained liver injury and chr...

Pan-cancer Analyses Refine the Single-Cell Portrait of Tumor-Infiltrating Dendritic Cells.

Dendritic cells (DCs) are pivotal orchestrators of anti-tumor immunity. DC-based anti-tumor treatmen...

A hybrid supervised and unsupervised machine learning approach for identifying nucleoside drugs using nanopore readouts.

Nucleoside drugs, mimics of natural nucleosides, have become cornerstone treatments in clinical appr...

Optimizing space heating efficiency in sustainable building design a multi criteria decision making approach with model predictive control.

Efficient space heating is vital for sustainable building design, offering opportunities to reduce e...

Investigating the impact of social media images on users' sentiments towards sociopolitical events based on deep artificial intelligence.

This paper presents the findings of the research aimed at investigating the influence of visual cont...

Electrical stimulation of stem cell-derived human neural networks for evaluating anti-seizure medications.

OBJECTIVE: Current preclinical epilepsy drug screening relies on animal models that poorly reflect h...

Recent Advances of Microcapsule-based Intelligent Coatings: From Bioinspired Designs, Material Selections, to Potential Applications.

Coating technology is widely used in diverse fields such as energy, healthcare, and aerospace becaus...

A fair machine learning model to predict flares of systemic lupus erythematosus.

OBJECTIVE: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that disproportionatel...

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 caus...

Machine learning-assisted tacrolimus dose optimization in childhood- onset systemic lupus erythematosus through population pharmacokinetic modeling.

OBJECTIVE: This study aimed to improve treatment effectiveness in childhood-onset systemic lupus ery...

Discovery of protein lactylation-associated biomarkers and their potential pathogenic mechanisms in recurrent spontaneous abortion.

Protein lactylation plays a critical regulatory role in various human diseases; however, its functio...

AI-based virtual immunocytochemistry for rapid and robust fine needle aspiration biopsy diagnosis.

Presently, pathologists need to stain biopsy samples with standard and antibody-based immunocytochem...

Anti-Quasisynchronization for Asynchronous Leader-Follower Markovian Neural Networks With Hidden Markov Model-Based Intermittent Control.

This study focuses on anti-quasisynchronization for discrete-time asynchronous leader-follower Marko...

Developing angiogenesis-related prognostic biomarkers and therapeutic strategies in bladder cancer using deep learning and machine learning.

Bladder cancer (BLCA) is a prevalent urological malignancy that exhibits a high degree of tumor hete...

Comparative effectiveness of anti-seizure medications in emulated trials using medical informatics.

Anti-seizure medications (ASMs) are often prescribed using a trial-and-error approach with a similar...

BertADP: a fine-tuned protein language model for anti-diabetic peptide prediction.

BACKGROUND: Diabetes is a global metabolic disease that urgently calls for the development of new an...

NeXtMD: a new generation of machine learning and deep learning stacked hybrid framework for accurate identification of anti-inflammatory peptides.

BACKGROUND: Accurate identification of anti-inflammatory peptides (AIPs) is crucial for drug develop...

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