Prescriptions

Asymmetric Drug-Drug Interaction Prediction Based on Generative Adversarial Networks and Knowledge Graph.

Drug-drug interaction (DDI) prediction remains a significant challenge due to the complexity of biological systems and the growing demand for precise predictions. Recent advances in deep learning have been successfully applied to DDI prediction. However, the asymmetrical nature of DDIs is always neglected, which can lead to some information loss during the feature learning process. To address the ...

Fully automatic left ventricle segmentation in [Formula: see text]Rb PET/CT Using a semi-supervised nnU-net.

BACKGROUND: Quantification of myocardial blood flow (MBF) with [Formula: see text]Rb PET/CT requires accurate delineation of the left ventricle (LV). Manual or semi-automated contouring remains time-consuming and error-prone, particularly in hypoperfused myocardium. We developed and validated a fully automatic LV segmentation pipeline using nnU-Net applied to [Formula: see text]Rb PET/CT. A manual...

MoS2 Heterojunction-Based Gas Sensor Platform Enables Real-Time Detection of Sarin at Room Temperature via Strong Adsorption and Enhanced Charge Transfer.

Chemical warfare agents (CWAs) are still a serious threat to human safety with high toxicity and ease of preparation. Developing room-temperature sens...

Improving Clinical Efficiency Using Artificial Intelligence Scribe for Documentation (ICE-AID Study): A Retrospective-Prospective Cohort Study at a Quaternary Children's Hospital and Health Service.

AIM: To evaluate the impact of an artificial intelligence medical scribe (AIMS) on clinical documentation efficiency, document quality, clinician-pati...

Incorporating geospatial environmental exposure indicators in individual hypertension risk prediction: a multi-stage machine learning pipeline.

BACKGROUND: Environmental exposures are known contributors to chronic disease but are rarely incorporated into risk prediction models. OBJECTIVE: We d...

Decoding lactylation heterogeneity in glioblastoma: machine learning identifies G6PC3 as a prognostic target.

BACKGROUND: Glioblastoma (GBM) is the most common malignant glioma in adults. It has an extremely poor prognosis, highlighting an urgent need for new ...

Self-Reported Health Outcomes in Metabolic Health YouTube Comments: Cross-Sectional Study and Rule-Based Natural Language Processing Framework Development and Validation.

BACKGROUND: YouTube is increasingly used for healthcasting, the sharing of evidence-based dietary and lifestyle interventions by domain experts. In th...

Predicting immune checkpoint inhibitor cardiotoxicity using machine learning: a systematic review of model performance and methodological quality.

BACKGROUND: Immune checkpoint inhibitors (ICIs) significantly improve cancer outcomes but can cause rare, potentially fatal cardiotoxicity, including ...

Local control and dose selection for lung cancer brain metastases treated with radiosurgery: an artificial intelligence model.

Clinical and radiological outcomes after Stereotactic radiosurgery (SRS) for lung cancer brain metastases are heterogeneous, and prescription dose sel...

Enabling Drug-Drug Interaction Event Prediction with Multi-view-enhanced Chemical Structural Information.

Predicting drug-drug interaction (DDI) events is critical for ensuring patient safety, optimizing therapeutic efficacy, and advancing drug discovery. ...

When AI Colludes: Clinical Reliability of Training and Preference Data as a Trustworthy-AI Criterion.

Research on artificial intelligence (AI) and mental health has focused largely on harms at deployment, including chatbot safety, sycophancy, and AI-as...

Large Language Model-Generated Patient Instructions for Prescriptions in Primary Health Care: Preclinical Algorithm Validation.

BACKGROUND: The application of generative artificial intelligence to simplify medication use instructions has the potential to enhance people's health...

Addendum to "Predicting treatment pathways in Class II malocclusion patients using machine learning: A comparative study of four algorithms for classifying camouflage, growth modulation, and surgical decisions" [Int Orthod. 24 (2026) 101070].

OBJECTIVES: The aim of this study was to develop a machine learning model to assist in treatment decision-making for surgery, camouflage, and growth m...

Methods for determining indications for antibiotic prescriptions to facilitate antimicrobial stewardship: a scoping review.

BACKGROUND: Effective antimicrobial stewardship (AMS) requires accurate information on the reason for prescribing antimicrobials. To design targeted i...

Insights From Spatiality: Accelerating Pharmaceutical Research Using Mass Spectrometry Imaging.

Mass spectrometry imaging (MSI) has emerged as a transformative technology in pharmaceutical research, offering unprecedented capabilities to visualiz...

Enhancing Early Prediction of Gestational Diabetes Mellitus Through Data Augmentation and Feature Guidance: Model Development and Validation Study.

BACKGROUND: Early prediction of gestational diabetes mellitus (GDM) is critical for improving maternal health outcomes. However, predictive models are...

An analysis of the influence of perceptual dimensions in biomimetic packaging design on generation Z consumers' flow experiences using PLS-SEM, ANN, and fsQCA.

Physical packaging has evolved into a central medium for deep interaction between brands and consumers. While biomimetic design offers cross-disciplin...

Standardizing antiviral response metrics for mono- and combination therapies in acute, chronic and latent viral infections.

The COVID-19 pandemic showed that heterogeneous antiviral assay designs, endpoints and reporting practices can obscure which candidate drugs and combi...

Benchmarking Nanoscale Noncovalent Complexes at the Two-Hundred-Atom Scale with Converged Local CCSD(T).

We present vL27, a benchmark data set of 27 large noncovalent complexes with sizes up to 205 atoms, designed to probe nanoscale interaction effects. R...

Platelets as Programmable Drug Depots: Toward Predictive and Mechanistic Drug Loading.

Efficient drug delivery remains a major challenge in pharmaceutical science, with synthetic nanocarriers often facing limitations in real biological s...