Ethics

Innovative teaching in legal medicine through forensic simulation: a case-based educational project.

In Italy, forensic medicine education is traditionally theory-based, which limits students' access to practical experiences due to confidentiality constraints and the complexity of real cases. This paper describes a forensic simulation conducted at the Clinical Simulation Center of the Campus Bio-Medico University of Rome, designed to offer students a structured opportunity to apply their theoreti...

Artificial intelligence-enabled digital reproductive health education: corpus-based strategies for strengthening Spanish health communication capacity.

This study examines how corpus-grounded artificial intelligence (AI) can strengthen Spanish reproductive health communication capacity within China's digital health ecosystem. A mixed-methods design was employed, combining corpus linguistics, AI-assisted message generation, expert-informed evaluation, and quantitative user assessment. A domain-specific Spanish reproductive health corpus was constr...

Machine Learning Accelerated Non-Adiabatic Molecular Dynamics Elucidates Local Polarization Effects on Non-radiative Recombination in Halide Perovskites.

Non-radiative recombination is a critical factor limiting the optoelectronic performance of halide perovskites, yet how local polarization induced by ...

Toward equitable digital health: an integrated framework addressing exclusion, ethics, and implementation across healthcare systems.

BACKGROUND: Digital health technologies are fundamentally reshaping healthcare delivery, access, and governance worldwide. While these innovations off...

Towards the design of artificial sensing materials via quantum-informed explainable AI.

Computational design of sensing materials remains fundamentally challenging due to the vast configurational landscape and the absence of robust proper...

Personalized non-invasive continuous glucose monitoring via multiparameter-informed machine learning.

Non-invasive continuous glucose monitoring (NCGM) based on reverse iontophoresis (RI) holds considerable promise for diabetes management; however, its...

Improving healthcare professionals' usage of artificial intelligence-powered risk recommenders through enhancement of trust and acceptance: a rapid realist review protocol.

INTRODUCTION: Healthcare professionals working in busy hospital environments are expected to make multiple back-to-back critical decisions related to ...

A blockchain-assisted secure federated learning architecture for intrusion detection in internet of things networks.

The fast growth of Internet of Things (IoT) systems has made them very susceptible to advanced cyber-attacks, and an intelligent and privacy-sustainab...

Prediction of antibody non-specificity using protein language models and biophysical parameters.

The development of therapeutic antibodies requires optimizing target binding affinity and pharmacodynamics, while ensuring high developability potenti...

AI-assisted health management and older adults' autonomy: an empirical ethics study of privacy, algorithmic reliance, and relational dynamics.

BACKGROUND: AI-assisted health management is increasingly integrated into healthcare practices for older adults, offering new possibilities for contin...

An AI-Enabled Predictive Harm Response Management Algorithmic Tool to Reduce Adverse Events in Health Care Settings (PreHaRM): Protocol for a Three-Phase Model Development and Pilot-Testing Study.

BACKGROUND: Current data analysis and coordination methods do not effectively support nurses and midwives in risk reduction, as retrospective reportin...

Coconstructing CHAMP, an Artificial Intelligence Chatbot for Pediatric Infectious Symptoms Management: Protocol for a Multiphase Participatory Study.

BACKGROUND: Acute infectious symptoms are a leading cause of pediatric emergency department visits in Canada, many of which are low acuity and could b...

Artificial intelligence policy among nursing journals.

BACKGROUND: The rapid integration of generative artificial intelligence (AI) into scholarly work is reshaping nursing publication standards. PURPOSE: ...

Personalized prediction of student progress in moral education using multi modal learning.

In modern education systems, accurate and individualized prediction of the development of students in ethics education is the central problem. Unbiase...

Leveraging the non-contrast CT component of PET/CT: an AI-driven delta-radiomics approach to monitor treatment response in metastatic breast cancer.

PURPOSE: 18 F-FDG PET/CT is the standard modality for monitoring treatment response in metastatic breast cancer. This study aims to evaluate the predi...

Ethics and Fairness Considerations in AI-Based Deception Detection Technologies for Mental Health Applications: Focus Group Study.

BACKGROUND: Artificial intelligence (AI) technologies are increasingly being integrated into mental health settings to support tasks such as clinical ...

Uncovering subgroup heterogeneity in dyslexia intervention outcomes using explainable machine learning.

Identifying heterogeneity within literacy intervention outcomes can inform more targeted strategies for dyslexia remediation. Based on prior work that...

FL-trafficNet: a hybrid federated transformer-GNN framework with dual attention for smart routing in IoV and VANET environments.

One of the major problems smart cities face is how to efficiently route traffic, especially when connected vehicles and sensors produce a very large a...

Parallel AI-driven framework for post-quantum secure medical image communication using swin-transformer restoration.

Reliable and secure transmission of medical images is essential for telemedicine, remote diagnosis, and distributed healthcare systems. However, medic...

Future Pharmacists in the Age of Artificial Intelligence: A Mixed-Methods Study of First-Year Students in Vietnam.

OBJECTIVES: To assess AI readiness, perceptions, and usage patterns among first-year pharmacy students, and to identify factors associated with AI eng...