Prescriptions

MoGraphDRP: Multi-omics and graph fusion with bilinear attention for predicting drug sensitivity.

Accurate prediction of drug response in cancer cells is a fundamental step toward achieving precision medicine and designing personalized therapies. In this study, a multi-branch deep learning framework is proposed that integrates multi-omics cellular data including gene expression, mutation, methylation, and biological pathways with structural features of drugs (molecular graphs and various chemi...

Cross-Cultural Differences in Public Discourse on COVID-19 Vaccination in the United States and South Korea: Cross-Sectional Analysis Using Natural Language Processing.

BACKGROUND: The COVID-19 vaccine was introduced as a crucial tool to combat the pandemic. However, concerns about its effectiveness, side effects, and misinformation spread remain. Prior research largely relied on survey-based approaches with limited populations. To address these limitations, social media offers a broader, more naturalistic lens into public discourse on COVID-19 vaccination. Accor...

Association of diabetes severity with cognitive function in US adults: a cross-sectional analysis of the AI-READI multicentre cohort.

OBJECTIVES: To evaluate whether type 2 diabetes mellitus (T2DM) presence and severity are associated with differences in global and domain-specific co...

Automated interpretable artificial intelligence genomic prediction with AIGP.

Predicting phenotypes from genomic mutations remains a major genetic challenge. Traditional statistical methods (such as GBLUP and BayesR) have limita...

Twin cross contrastive learning with multi-modality fusion for drug-target affinity prediction.

Accurate prediction of drug-target binding affinity (DTA) can provide valuable insights for accelerating drug discovery and repositioning. While deep ...

Assessment of socioeconomic and demographic risk factors for low birth weight using model-agnostic explainable ensembles.

BACKGROUND AND OBJECTIVE: Low birth weight (LBW) is a major global public health concern, strongly linked to neonatal morbidity and long-term health c...

Harnessing the gut-heart axis for cardiovascular drug innovation: microbiome, metabolites, and personalized treatment strategies.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide despite major advances in pharmacotherapy. Emerging evidence reveals a p...

Digital breast tomosynthesis and reading with artificial intelligence.

Digital breast tomosynthesis (DBT) increases sensitivity and specificity compared to digital mammography (DM) in the early detection of breast cancer....

Design and Optimization of Indomethacin Nanocrystals using Machine Learning and Molecular Dynamics Simulations.

In this study, a stable nanocrystalline drug delivery system for indomethacin (IND) was rapidly developed by integrating machine learning methods with...

Uncertainty-aware hybrid deep generative framework for robust and explainable drug discovery.

Conventional techniques in drug discovery are time-consuming and less accurate due to the vast chemical space and associated uncertainty. Artificial i...

Real-time digital prescriptions unlock influenza dynamics: evidence from 21 million transactions.

Traditional influenza surveillance suffers from 1-2 week reporting delays that compromise outbreak response. We analyzed 21.08 million digital prescri...

A deep-learning-based early warning system for abnormal eye conditions in chickens.

In current poultry production practice, farmers are required to frequently enter their poultry houses and visually inspect their chickens to assess fl...

An AI-based approach accelerates the discovery of protein-protein interaction modulators targeting NCS-1.

Drug repurposing is an efficient strategy to accelerate the identification of therapeutic compounds by finding new uses for existing drugs. Here, we l...

Hybrid lightweight vision transformers with attention mechanism for feature extraction and classification of product designs.

In modern consumer markets, product packaging strongly influences customer attention and buying decisions. Attractive and informative designs help bra...

Construction of air quality health index based on multi-pollutant Bayesian kernel machine regression and deep learning early warning framework.

BACKGROUND: Efficient characterization and early warning of health risks associated with air pollution are critical issues in public health management...

BESTDR Enables Bayesian Quantification of Mechanism-Specific Drug Responses.

UNLABELLED: Understanding drug responses at the cellular level is essential for elucidating mechanisms of action and advancing preclinical drug develo...

Physics-Constrained Deep Learning for Effective Atomic Number and Density Calculation of Biological Tissues in Photon-Counting Spectral CT.

Photon-Counting Detector Computed Tomography (PCD-CT) boasts excellent spectral utilization capability. Combined with material decomposition methods, ...

Optimization of drug diffusion in drug-eluting stents for coronary artery based on deep reinforcement learning.

Drug-eluting stents (DES) are extensively used to treat coronary artery disease, and improving their therapeutic efficacy remains a long-standing rese...

Adverse reactions of PD-1/PD-L1 inhibitors in cancer: FAERS database analysis and protocols to mitigate immune-related events in elderly patients and when using pembrolizumab and atezolizumab.

OBJECTIVE: This study aimed to characterize adverse drug reactions (ADRs) associated with programmed death-1/programmed death-ligand 1 (PD-1/PD-L1) in...

Foot Progression Angle Modulates Three-Dimensional Lower-Limb Biomechanics in Flexible Flatfoot: Kinematic-Kinetic Patterns and Clinical Implications.

INTRODUCTION: Foot progression angle affects gait and lowerlimb alignment. Altered angles may increase knee and ankle loading and produce tissue loadi...