US Health Policy

Human-AI Interaction in Low- and Middle-Income Countries: Qualitative Study of How Local Human Factors Influence AI Development and Deployment.

BACKGROUND: Artificial intelligence (AI) is rapidly transforming health care and health research, offering new opportunities for improving efficiency, accessibility, and equity. However, the ethical, societal, and regulatory challenges of AI development and deployment are particularly pronounced in low- and middle-income countries (LMICs). While existing literature often emphasizes high-level ethi...

Harnessing ChatGPT for SBA question writing: a novel approach to medical student learning.

The introduction of the Medical Licensing Assessment (MLA) requires UK medical graduates to pass two 100-item single best answer (SBA) question papers. Access to high-quality question banks is often restricted by expensive paywalls, evolving guidelines, and institutional safeguarding of questions for future assessments. This limits students' ability to practice exam-style questions and develop the...

Long-term exposure to wildfire smoke particulate matter and incident stroke: a US nationwide study.

BACKGROUND AND AIMS: Wildfire smoke is a growing public health concern, particularly due to its high fine particulate matter (PM2.5) concentrations. W...

IHGCN-PLA: An interpretable heterogeneous graph convolutional network for protein-ligand binding affinity prediction with multimodal interaction fusion.

Protein-ligand binding affinity prediction is fundamental to computer-aided drug discovery, enabling accelerated therapeutic development at reduced co...

Quantifying the AI readiness gap: An international, multidisciplinary assessment of artificial intelligence literacy in the radiation oncology community.

PURPOSE: The rapid integration of artificial intelligence (AI) into imaging-intensive fields like radiation oncology (RO) is transforming the clinical...

An Interpretable Multidimensional Acoustic Physiology Map for COPD Using Digital Lung Sounds.

BACKGROUND: Lung sound analysis may capture chronic obstructive pulmonary disease (COPD) related physiology, but many methods are hard to interpret cl...

Using an educator-guided generative artificial intelligence (GenAI) tool for developing communication skills in undergraduate pharmacy students.

INTRODUCTION: Effective communication of health messages is essential. Pharmacy educators face the challenge of adapting curricula or integrating Gene...

Beyond clinical predictors: Determining the impact of psychosocial factors in chronic pain after spinal cord injury.

UNLABELLED: ▒: Although chronic pain is common after traumatic SCI, prognostic models have traditionally prioritized clinical injury characteristics, ...

ABCC2 as a novel therapeutic target in lung adenocarcinoma: a machine learning-driven discovery linking ammonia metabolism to prognosis and drug resistance.

BACKGROUND: Ammonia, long regarded as a metabolic waste product, has recently been recognized as a pivotal oncometabolite in the tumor microenvironmen...

Investigating the Quality of Chat Generative Pretrained Transformer's Parenting Advice.

OBJECTIVES: Chat Generative Pretrained Transformer (ChatGPT) is a widely adopted tool that can provide immediate parenting guidance. The aim of this s...

Artificial intelligence in cardiovascular care for internal medicine: from promising algorithms to useful clinical services.

Artificial intelligence is expanding rapidly in cardiovascular medicine, but its value in internal medicine depends less on raw model performance than...

Why are rural hospitals closing in the U.S.? Predictors identified using explainable machine learning.

OBJECTIVE: Rural hospital closures in the U.S. reduce access to essential healthcare services and worsen health and economic outcomes in rural communi...

AI-assisted teams outperform AI-led teams but not human-only teams in assessing research reproducibility in quantitative social science.

Large Language Models (LLMs) such as ChatGPT are transforming how scientists conduct and validate research, offering promise as tools to improve scien...

Translating transcriptomics analysis into diagnostic workflows: clinical variant identification and interpretation in hypothesis-driven and hypothesis-free approaches.

BACKGROUND: Despite significant advancements in genetic diagnosis, there are still bottlenecks in DNA-level testing. Challenges to diagnosis include t...

Innovation and Our Data: This Does Not Need to Be Scary.

The rapid emergence of Artificial Intelligence (AI) has unveiled the clinical, public health, and economic value of Canada's health data assets. Howev...

Reported trust varies with graded value alignment in AI-attributed economic-environmental choices.

As artificial intelligence (AI) systems increasingly support value-laden decisions, users may judge whether an advisor's observable choices align with...

Measuring Radiology's Impact: Core Concepts for Tracking Patient-Oriented Outcomes and Delivering High-Value Care-A Perspective by the ACR's Relevance and Impact Committee.

Radiology strongly impacts patient care. However, radiologists' potential to promote high-value care has long been underappreciated, partly related to...

Lessons from the first U.S. school districts with real-time indoor environmental quality (IEQ) sensors in classrooms: benefits, barriers and opportunities.

With aging buildings, rising temperatures, and limited budgets, school districts in the United States need effective strategies to address classroom e...

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 ...

FA-SedLoRA: scene-driven fine-tuning and style disentanglement for domain-generalized cardiac MRI segmentation.

The advent of deep learning has significantly advanced the state of the art in cardiac magnetic resonance (CMR) image segmentation. However, most mode...