Prescriptions

Towards convergence of AI and blockchain for personalized medicine in pharmacogenomics.

The health informatics field's pursuit of personalized healthcare continuously faces constraints from patients, clinicians, and resource limitations. Recent advances in artificial intelligence (AI) and machine learning (ML) models have led to their widespread adoption in personalized genomic research for their outstanding predictive capabilities for drug responses to assist in personalized healthc...

FLOWR: flow matching for structure-aware de novo, interaction- and fragment-based ligand generation.

Here we introduce FLOWR, a structure-based framework for the generation and optimization of three-dimensional ligands. FLOWR integrates continuous and categorical flow matching with equivariant optimal transport, enhanced by an efficient protein pocket conditioning. Alongside FLOWR, we present SPINDR, a curated dataset comprising ligand-pocket cocrystal complexes specifically designed to address e...

Demographic prompt cues shift clinical recommendations in multimodal large language models: a multi-model audit of 25,380 dental radiograph assessments.

BACKGROUND: Multimodal large language models (LLMs) are increasingly being evaluated for clinical image interpretation, but whether patient demographi...

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 ...

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). ...

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...

Comparative evaluation of handwriting recognition by large language models (LLMs) in interpreting handwritten medication lists.

INTRODUCTION: Handwritten bedside medication lists remain common in healthcare, especially in low-resource countries, presenting challenges for digiti...

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...

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...