Rheumatology

Lupus

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

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Optical Synaptic Devices with Multiple Encryption Features Based on SERS-Revealed Charge-Transfer Mechanism.

2D optical synaptic devices with atomic-scale thickness show potential for building highly integrate...

Application of machine learning in assessing disease activity in SLE.

OBJECTIVE: SLE is a chronic autoimmune disease with immune complex deposition in various organs, cau...

Can artificial ıntelligence detect the anti-aging effect of rhinoplasty?

BACKGROUND: The quest for eternal youth has been a common theme in many cultures for centuries. Whil...

What is the doggest dog? Examination of typicality perception in ImageNet-trained networks.

Due to the emergence of numerous model architectures in recent years, researchers finally have acces...

Role of eccentricity based topological descriptors to predict anti-HIV drugs attributes with supervised machine learning algorithms.

Chemical graphs are mathematical representations of molecular structures, where atoms are represente...

Identification of glucocorticoid-related genes in systemic lupus erythematosus using bioinformatics analysis and machine learning.

BACKGROUND: Systemic lupus erythematosus (SLE) is a complex autoimmune disease that has significant ...

Unveiling CNS cell morphology with deep learning: A gateway to anti-inflammatory compound screening.

Deciphering the complex relationships between cellular morphology and phenotypic manifestations is c...

Artificial intelligence in anti-obesity drug discovery: unlocking next-generation therapeutics.

Obesity, a multifactorial disease linked to severe health risks, requires innovative treatments beyo...

Histopathology based AI model predicts anti-angiogenic therapy response in renal cancer clinical trial.

Anti-angiogenic (AA) therapy is a cornerstone of metastatic clear cell renal cell carcinoma (ccRCC) ...

Enhancing short-term algal bloom forecasting through an anti-mimicking hybrid deep learning method.

Accurately predicting algal blooms remains a critical challenge due to their dynamic and non-station...

CPHNet: a novel pipeline for anti-HAPE drug screening via deep learning-based Cell Painting scoring.

BACKGROUND: High altitude pulmonary edema (HAPE) poses a significant medical challenge to individual...

Screening and validating genes associated with cuproptosis in systemic lupus erythematosus by expression profiling combined with machine learning.

Cell death has long been a focal point in life sciences research, and recently, scientists have disc...

TARSL: Triple-Attention Cross-Network Representation Learning to Predict Synthetic Lethality for Anti-Cancer Drug Discovery.

Cancer is a multifaceted disease that results from co-mutations of multi biological molecules. A pro...

Retinal Vascularization Rate Predicts Retinopathy of Prematurity and Remains Unaffected by Low-Dose Bevacizumab Treatment.

PURPOSE: To assess the rate of retinal vascularization derived from ultra-widefield (UWF) imaging-ba...

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) (...

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...

A new era of psoriasis treatment: Drug repurposing through the lens of nanotechnology and machine learning.

Psoriasis is a persistent inflammatory skin disorder characterized by hyper-proliferation and abnorm...

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