Prescriptions

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 cognitive function among US adults, using standardised Montreal Cognitive Assessment (MoCA) testing. DESIGN: Cross-sectional study SETTING: Three U.S academic medical centres participating in the Artificial Intelligence-Ready and Equitable Atlas for Di...

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 limitations, including reliance on artificial prior assumptions, and hard to capture epistatic effects. Machine learning (ML) has emerged as a powerful alternative for genomic prediction; however, it often struggles with interpretability because of its bla...

Dynamic coactivation patterns during repetitive negative thinking: A cross-sectional fMRI study.

BACKGROUND: Repetitive negative thinking (RNT) and neuroticism are risk factors for internalizing psychopathology. However, their interaction has only...

MLGT: A multimodal graph attention network for virtual screening of anti-Uveitis drugs.

Uveitis is a severe ocular inflammatory disease with complex immune-mediated pathogenesis, posing significant challenges for drug discovery. While art...

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...

WGB-GLFI: A Novel Graph-Based Global-Local Feature Interaction Framework for Automated Seizure Detection.

Epilepsy detection faces significant challenges due to unpredictable seizures, ranging from brief awareness lapses to severe convulsions, posing risks...

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...

Advancing metal organic frameworks screening and remediation condition optimization for removing persistent organic pollutant via integrated machine learning and theoretical calculation insights.

Metal organic frameworks (MOF) have become increasingly important for removing persistent organic pollutants (POPs). However, achieving precise and ra...

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...