Lupus

Prediction of Anti-rheumatoid Arthritis Natural Products of Xanthocerais Lignum Based on LC-MS and Artificial Intelligence.

AIMS: Employing the technique of liquid chromatography-mass spectrometry (LCMS) in conjunction with ...

Multi-Omics Integration With Machine Learning Identified Early Diabetic Retinopathy, Diabetic Macula Edema and Anti-VEGF Treatment Response.

PURPOSE: Identify optimal metabolic features and pathways across diabetic retinopathy (DR) stages, d...

Deciphering the Role of SLFN12: A Novel Biomarker for Predicting Immunotherapy Outcomes in Glioma Patients Through Artificial Intelligence.

Gliomas are the most prevalent form of primary brain tumours. Recently, targeting the PD-1 pathway w...

An evolving machine-learning-based algorithm to early predict response to anti-CGRP monoclonal antibodies in patients with migraine.

BACKGROUND: The present study aimed to determine whether machine-learning (ML)-based models can pred...

Explainable deep neural networks for predicting sample phenotypes from single-cell transcriptomics.

Recent advances in single-cell RNA-Sequencing (scRNA-Seq) technologies have revolutionized our abili...

A transformer-based deep learning survival prediction model and an explainable XGBoost anti-PD-1/PD-L1 outcome prediction model based on the cGAS-STING-centered pathways in hepatocellular carcinoma.

Recent studies suggest cGAS-STING pathway may play a crucial role in the genesis and development of ...

Machine learning-enabled virtual screening indicates the anti-tuberculosis activity of aldoxorubicin and quarfloxin with verification by molecular docking, molecular dynamics simulations, and biological evaluations.

Drug resistance in Mycobacterium tuberculosis (Mtb) is a significant challenge in the control and tr...

A Comprehensive Natural Language Processing Pipeline for the Chronic Lupus Disease.

Electronic Health Records (EHRs) contain a wealth of unstructured patient data, making it challengin...

Exploring Offline Large Language Models for Clinical Information Extraction: A Study of Renal Histopathological Reports of Lupus Nephritis Patients.

Open source, lightweight and offline generative large language models (LLMs) hold promise for clinic...

Identification of novel biomarkers for childhood-onset systemic lupus erythematosus using machine learning algorithms and immune infiltration analysis.

BACKGROUND: Childhood-onset systemic lupus erythematosus (cSLE) is a chronic autoimmune disease that...

Trust me if you can: a survey on reliability and interpretability of machine learning approaches for drug sensitivity prediction in cancer.

With the ever-increasing number of artificial intelligence (AI) systems, mitigating risks associated...

Efficient Normalized Conformal Prediction and Uncertainty Quantification for Anti-Cancer Drug Sensitivity Prediction with Deep Regression Forests.

Deep learning models are being adopted and applied across various critical medical tasks, yet they a...

Fatigue Detection with Machine Learning Approaches using Data from Wearable Devices.

Severe and chronic fatigue is one of the top symptoms in patients with non-communicable chronic immu...

From machine learning to clinical practice: phenotypic clusters of anti-MDA5 antibody-positive dermatomyositis.

Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer.

Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans ...

Characterizing Anti-Vaping Posts for Effective Communication on Instagram Using Multimodal Deep Learning.

INTRODUCTION: Instagram is a popular social networking platform for sharing photos with a large prop...

AgeAnnoMO: a knowledgebase of multi-omics annotation for animal aging.

Aging entails gradual functional decline influenced by interconnected factors. Multiple hallmarks pr...

USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING APPROACHES TO ENHANCE CANCER THERAPY AND DRUG DISCOVERY: A NARRATIVE REVIEW.

BACKGROUND: This paper looks at how AI and machine learning have been applied over the last ten year...

Artificial Intelligence Application for Anti-tumor Drug Synergy Prediction.

Currently, the main therapeutic methods for cancer include surgery, radiation therapy, and chemother...

PD-1 Targeted Antibody Discovery Using AI Protein Diffusion.

The programmed cell death protein 1 (PD-1, CD279) is an important therapeutic target in many oncolog...

In-silico prediction of anti-breast cancer activity of ginger (Zingiber officinale) using machine learning techniques.

INTRODUCTION: Indonesian civilization extensively uses traditional medicine to cure illnesses and pr...