Cultural Competence

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 offer unprecedented opportunities to extend services, particularly in resource-constrained settings, early implementation experiences from large-scale platforms such as India's Co-WIN vaccination system and the Ayushman Bharat Digital Mission (ABDM) rev...

Integrated analysis of human-mouse gut microbiota in RSV infection based on machine learning.

BACKGROUND: Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infections in children, but effective treatment options remain limited. The gut-lung axis, which highlights the role of gut microbiota in regulating respiratory immunity, provides new opportunities for developing probiotic-based therapies. However, existing studies on RSV-associated gut microbiota are often...

Language barriers, mobility, and health equity: clinical risks, economic burden, and policy options for universal language access.

BACKGROUND: International mobility has intensified routine contact between health systems and patients who do not speak the dominant language of care....

Molecular prevalence, genomic characterization, and zoonotic potential of novel paramyxovirus and hepacivirus in Alexandromys fortis, Republic of Korea.

Rodents are substantial reservoirs of zoonotic viruses with regular human exposure restricted to a limited number of species. Numerous rodent species ...

Can Digital Tools Fix Bias in Mental Health Triage?

Recent advances in digital technologies hold both promise and potential pitfalls for mental health triage. In this News and Perspectives article, JMIR...

Quality and performance of machine learning versus logistic regression for predicting IVIG resistance in Kawasaki disease: a PROBAST+AI systematic comparison.

BACKGROUND: This study aimed to systematically compare the predictive performance and methodological quality of logistic regression (LR) and machine l...

Usability and Usefulness of Machine Learning-Based Clinical Decision Support Software in Primary Care: Survey of Users in a Prospective Observational Study.

BACKGROUND: The successful implementation of decision support systems promises to enhance high-quality care. However, the successful implementation of...

Artificial intelligence for reducing metal artifacts in dental CBCT images: a systematic review.

OBJECTIVES: The presence of metallic restorations introduces severe artifacts that compromise diagnostic accuracy of cone beam computed tomography (CB...

Genome-wide analysis of the invasive fungal pathogen Neopestalotiopsis reveals high genomic diversity, effector repertoires, and the assessment of fungicide resistance risks.

Neopestalotiopsis species (spp.) have recently emerged as major pathogens worldwide, causing leaf spot, fruit rot, and crown rot of strawberry, result...

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 ...

Multidomain correlates of burnout: A population-based study using supervised machine learning.

PURPOSE: Burnout is a growing challenge for individuals and society and understanding risk factors is crucial to develop targeted prevention strategie...

Cultural bias in large language models' ability to follow neuroradiology guidelines.

OBJECTIVES: Large language models (LLMs) are increasingly explored as decision-support tools in medical imaging. However, their ability to align with ...

'Man vs. Machine: can ML algorithms diagnose headaches as accurately as clinicians? A systematic review.'.

BACKGROUND: Headache disorders are frequently misdiagnosed. We aimed to systematically evaluate the diagnostic accuracy, methodological quality, and c...

Explainability in context: calibrating appropriate trust and reliance in artificial intelligence.

BACKGROUND AND SIGNIFICANCE: Predictive artificial intelligence (AI) promises to transform care delivery, enhance patient safety, and improve health o...

Phosphorylation tunes strain-specific protein condensation during rotavirus replication organelle assembly.

In many viruses, intrinsically disordered proteins (IDPs) drive the formation of replicative organelles via liquid-liquid phase separation (LLPS). In ...

Overcoming LPS-mediated resistance in gram-negative pathogens: a review of LL-37 analogs and computational design strategies.

The increasing incidence of antimicrobial resistance (AMR) in Gram-negative bacteria has become a significant global health issue, driven primarily by...

BiasField: Interactive Bias Probing of Machine Learning Datasets.

Bias in machine learning datasets occurs when certain attributes are unfairly associated, e.g., serious males being mostly linked with law enforcement...

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 ...

Explainable Artificial Intelligence in Dentistry: A Systematic Review of Its Trust and Translation.

INTRODUCTION AND AIMS: Explainable artificial intelligence (XAI) is a set of methods and processes that make the decisions of artificial intelligence ...

Clin-STAR Corner: Practice Changing Advances at the Interface of Artificial Intelligence/Machine Learning and Geriatrics.

Artificial intelligence (AI) methods, including machine learning (ML), are transforming healthcare by enabling personalized interventions that integra...