Prescriptions

Enhancing anesthesia monitoring training: a SPOC and Gagné's model hybrid personalized by artificial intelligence.

BACKGROUND: High-quality training in anesthesia nursing-particularly in intraoperative monitoring-is essential for ensuring patient safety. However, the rapid shift toward online learning after COVID-19 has led to challenges such as reduced interaction, limited personalization, and decreased student engagement. Structured instructional models combined with artificial intelligence (AI)-based person...

Recent advances in redox-responsive polysaccharide-based nanostructures for cancer therapy.

Conventional tumor chemotherapy faces limitations including drug resistance, high toxicity, non-selectivity, and side effects. Nano-drug delivery systems (DDSs) demonstrate stronger efficacy via enhanced permeability and retention (EPR) effect in tumor vasculature. This review provides a comprehensive analysis of a promising solution: redox-responsive drug delivery systems engineered from biocompa...

Performance of Machine Learning Models in Predicting Outcomes After ACDF: A Systematic Review and Meta-Analysis of 443 000 Patients.

Study DesignSystematic review and meta-analysis.ObjectiveDirect head-to-head comparison of machine learning models aiming to predict outcomes in Anter...

Multidimensional analysis and predictive modeling of cognitive decline risk in the United States using propensity score matching and machine learning.

Cognitive decline, an early indicator of neurodegenerative disorders, presents a growing public health challenge. This study aimed to integrate causal...

Relation-aware pre-trained network with hierarchical aggregation mechanism for cold-start drug recommendation.

Drug recommendation systems have garnered considerable interest in the healthcare, striving to offer precise and customized drug prescriptions that al...

HybridDeepSynergy: A hybrid deep learning model integrating CNN, LSTM, and attention mechanisms for cancer drug synergy prediction.

A variety of AI-based approaches have been employed to analyze complex genomic datasets. Predicting the synergy of drug combinations is a critical ste...

An integrative multiomics random forest framework for robust biomarker discovery.

BACKGROUND: High-throughput technologies now produce a wide array of omics data, from genomic and transcriptomic profiles to epigenomic and proteomic ...

Machine Learning Model Predicts Recurrent Clostridioides difficile Infection in Patients With Inflammatory Bowel Disease (Recur CDI-IBD).

INTRODUCTION: Clostridioides difficile infection (CDI) present a significant challenge in patients with inflammatory bowel disease (IBD), with high re...

CompBind: Complex Guided Pretraining-Based Structure-Free Protein-Ligand Affinity Prediction.

Accurate prediction of protein-ligand binding affinity is essential in drug discovery. However, the limited availability and high cost of experimental...

PTET-DDI: Dual-Channel Drug-Drug Interaction Prediction with a Pre-Trained Language Model and Equivariant Graph Transformer.

Combination therapy is widely used in clinical practice, rendering accurate prediction of drug-drug interactions (DDIs) essential for treatment safety...

Psychiatric Documentation and Management in Primary Care With Artificial Intelligence Scribe Use.

IMPORTANCE: Despite increasingly widespread use of artificial intelligence (AI)-driven ambient scribes in medicine, the extent to which they are assoc...

An Explainable Molecular Token Estimation Method for Knowledge-aware Drug-Drug Interaction Prediction.

In molecular representation learning (MRL), tokens (e.g., atoms, motifs, and fingerprints) are the basic elements to represent molecules. It is a comm...

Machine Learning Prediction of Pharmacogenetic Testing Uptake Among Opioid-Prescribed Patients Using Electronic Health Records: Retrospective Cohort Study.

BACKGROUND: Opioids are a widely prescribed class of medication for pain management. However, they have variable efficacy and adverse effects among pa...

Transcriptomic profiling and machine learning uncover gene signatures of psoriasis endotypes and disease severity.

BACKGROUND: Despite increased understanding of psoriasis pathogenesis, molecular classification of clinical phenotypes and disease severity is poorly ...

Impact of patient communication style on agentic AI-generated clinical advice in E-medicine.

BACKGROUND: E-medicine use has surged, and health systems are exploring large language models (LLMs) for message triage. However, it is still unknown ...

Geometry-Enhanced Multiscale Joint Representation Learning for Drug-Target Interaction Prediction.

Drug-target interactions (DTIs) are the basis of the therapeutic effect of drugs, whose accurate prediction helps reduce the cost and time of experime...

Therapeutic nanofibrous scaffolds in precision drug delivery: formulation design, challenges and regulatory frameworks.

INTRODUCTION: Drug-loaded nanofibrous systems represent a breakthrough in drug delivery, overcoming limitations of conventional formulations. They dem...

A preregistered, open pipeline for early cerebral palsy risk assessment from Infant Videos.

Cerebral Palsy (CP), affecting approximately 1 in 500 children due to abnormal brain development, impacts movement control. Early risk assessment via ...

DeepHybridCPI: A hybrid deep learning framework for compound-protein interaction prediction.

In bioinformatics, deep learning-based methods for Compound-Protein Interaction (CPI) prediction play a vital role in virtual screening, drug discover...

Investigating the role of sensorimotor versus contextual cues in the sense of joint agency: a human-human and human-robot study.

Sense of Joint Agency (SoJA), is the feeling of control experienced by humans for their own, as well as their partner's actions, when acting in joint ...