Health Policy

Effectiveness of Artificial Intelligence-Assisted Peer Teaching in Orthopedic Clinical Education: Historical Cohort Study.

BACKGROUND: Peer teaching is an established pedagogical approach in medical education; yet, traditional methods face challenges including inconsistent knowledge support, variable teaching quality, and limited scalability. Artificial intelligence (AI) large language models offer potential to augment peer teaching by providing on-demand access to medical knowledge and clinical reasoning support. How...

Disparate privacy risks from medical AI.

Medical artificial intelligence (AI) models hold the promise to improve global access to high-quality diagnostics1. However, the training data underlying these models often contain sensitive patient information that may be exposed through privacy attacks2-7. Previous research has primarily quantified the success of these attacks in aggregate, across all records in a dataset. Thus, the privacy risk...

Unit dose drug dispensing systems in hospitals: a systematic review of medication error reduction and cost-effectiveness.

BACKGROUND: Medical errors pose significant risks to patient safety and public health. Automated unit dose drug dispensing systems (UDDSs) have emerge...

Artificial Intelligence in Health Technology Assessment Submissions: A Targeted Review of Global Policy and Practice.

OBJECTIVES: Artificial intelligence (AI) has the potential of revolutionizing healthcare, including health technology assessments (HTAs). Although its...

Quantifying the Economic Value of AI-Assisted Diabetic Retinopathy Screening: A Meta-Analysis Using the Incremental Net Benefit Framework.

OBJECTIVE: To quantitatively synthesize the economic value of artificial intelligence (AI)-assisted screening for diabetic retinopathy (DR), a leading...

Energy-efficient wireless network control via spatio-temporal deep learning and multi-agent reinforcement learning.

The rapid expansion of wireless data traffic is placing increasing strain on the energy consumption of current communication networks, intensifying th...

(Global) single market for data? Exploring data cosmopolitanism as a solidarity-based regulatory approach to the european health data space.

The European Union (EU) is advancing an interoperable data governance framework through the establishment of Common European Data Spaces (CEDS), foste...

Evaluating Large Language Models for Post-Publication Promotion: A Blinded Comparative Study of Social Media Posts in Public Health.

BACKGROUND: Social media platforms such as X (formerly Twitter) are increasingly used by journals, authors, and institutions to promote newly publishe...

A highly interpretable machine learning model for predicting lung cancer bone metastasis: uncovering the synergistic effect of routine biochemical markers.

BACKGROUND: Bone metastasis (BM) significantly impairs lung cancer prognosis and patient quality of life. Conventional imaging modalities often face l...

Solidarity or Segregation? ChatGPT Health and US Health Care Disparities.

ChatGPT Health, an artificial intelligence feature launched by OpenAI in January 2026, integrates personal medical records and consumer health data in...

Non-linear impact mechanisms of multi-modal urban traffic on air quality: An interpretable machine learning study for sustainable policy making.

Urban air pollution, specifically Nitrogen Dioxide (NO2), presents a multifaceted challenge that is intricately coupled with the stochastic, multi-mod...

Environmental sustainability in Somalia: the role of clean cooking energy and remittances on ecological footprints.

Environmental degradation in Somalia, driven primarily by reliance on biomass fuels and limited access to clean energy, poses a significant challenge ...

Quality metrics of synthetic radiomics data do not predict improvement under simulated external validation: an ecological fallacy across 50 public datasets.

OBJECTIVES: To investigate whether established synthetic data quality metrics predict when deep generative augmentation improves performance under sim...

Association between long-term PM2.5 exposure and risk of urinary tract infection in children: a nationwide longitudinal cohort study.

BACKGROUND: Urinary tract infection (UTI) is among the most common bacterial infections in children and can lead to both acute and chronic complicatio...

The Role of Artificial Intelligence in the Prevention of Intimate Partner Violence and Sexual Violence: A Scoping Review of the Literature.

Intimate partner and sexual violence (IPV/SV) remain pervasive global public health issues. Prevention efforts typically occur at the primary level (p...

Electronics with switchable flexibility for 3D conforming neural interfaces.

The intricate cortical folds of large primates physically restrict access to substantial portions of neural information via interface devices. Here, w...

Local performance and fairness testing of an AI Scribe in a paediatric developmental assessment clinic in South Australia: a silent trial protocol.

INTRODUCTION: Any tool that can reduce the administrative burden on healthcare providers while preserving safe, accountable and high-quality medical d...

MSCA-TNet based deep learning method for ECG arrhythmia classification.

Electrocardiography (ECG) is a widely adopted modality for monitoring cardiac rate and rhythm and identifying various abnormalities of the cardiac ele...

Automated extraction of colonoscopy quality indicators from free-text reports using a prompt-based large language model pipeline.

BACKGROUND AND AIMS: Artificial intelligence has increasingly enabled large-scale analysis of clinical documentation, offering new opportunities to im...

A validated custom pipeline for three-dimensional kidney stone renderings tocreate an open access repository.

Three-dimensional (3D) rendering of urologic pathology plays an important role in simulation-based education, surgical training, and computer vision r...