Public Health

Reduction in suicides and suicide attempts following implementation of AI-based video surveillance in the Stockholm metro system: an intervention study.

BACKGROUND: Over 700,000 suicides occurring globally each year are a major public health issue. Railways and metros provide a lethal means of suicide, mainly occurring by persons under train (PUT) events. Restriction of means has been shown to be effective in reducing suicides and is increasingly being prioritized in railway settings, e.g., using physical barriers. Here, we instead investigated th...

Balancing innovation and risk: artificial intelligence in travel medicine.

Artificial intelligence (AI) is increasingly influencing travel medicine, a field traditionally reliant on expert judgement and static guidelines. Machine learning systems, generative AI models and digital surveillance tools have the potential to enhance pre-travel counselling, improve diagnostic pathways and strengthen outbreak detection. However, concerns remain regarding variable performance, d...

Unraveling the adverse outcome pathways of metabolic dysfunction-associated steatotic liver disease triggered by environmental mixtures via biological knowledge-driven machine learning.

Environmental pollutant mixtures are potential risk factors for metabolic dysfunction-associated steatotic liver disease (MASLD), yet their joint effe...

From Cardioprotection to Trial Design: Rethinking Cardiac Safety in Oncology.

PURPOSE OF REVIEW: Cardio-oncology has emerged as a pivotal discipline aimed at preserving cardiovascular health in patients undergoing contemporary c...

The Development Path of Gynecological Cytology after Papanicolaou: from Bethesda to Artificial Intelligence and Personalized Medicine.

BACKGROUND: Cervical cancer is the fourth most common cancer whose incidence was significantly reduced with the help of Pap smear and organized cervic...

Time-series prediction of adverse birth outcomes in the U.S. using multilayer perceptron neural networks.

Adverse birth outcomes (ABOs), including preterm birth, low birth weight, low Apgar scores, and neonatal mortality, remain major public health challen...

Toward a global ecosystem for health professions education: harnessing open educational resources and generative AI with shared governance.

The global health workforce faces a projected shortage of more than 11 million health workers by 2030, with the most severe shortfalls in low- and mid...

Psoriatic Disease Across Dimensions: Global Epidemiology, Comorbidity, and Artificial Intelligence in Treatment Prediction.

The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2025 annual meeting featured a new "Soapbox: Rapid fire presentati...

The fetoneonatology fellowship: a unified subspecialty for the fetal-neonatal continuum.

Advances in fetal diagnosis and therapy have created a need for clinicians with expertise spanning prenatal assessment and neonatal care. Current mate...

User profiles of young breast cancer survivors on Chinese social media: machine learning-based text mining analysis study.

PURPOSE: Social media is vital for improving healthcare access, especially among disadvantaged groups. During the COVID-19 pandemic, young breast canc...

Postdeployment Monitoring and Surveillance Methods, Guidelines, and Possibilities for AI in Radiology.

As radiology AI systems move from predeployment validation to routine radiology practice, attention is shifting toward postdeployment monitoring and p...

Findings from the 2025 AMCP Foundation Symposium: Health Optimization 2.0.

The 2025 AMCP Foundation Symposium: Health Optimization 2.0 convened a select group of just over 70 managed care stakeholders in Dallas, Texas, on Dec...

Accurate focal-plane selection is crucial for artificial intelligence assessment of three-dimensional urine cytology specimens for bladder cancer screening and surveillance.

BACKGROUND: Bladder cancer is a common and highly recurrent malignancy requiring lifelong surveillance. Urine cytology serves as a noninvasive triage ...

Rapid whole-genome sequencing of Plasmodium DNA from cryptic malaria cases in UK travellers provides insights into infection origins, transmission and antimalarial resistance.

BACKGROUND: The UK reports approximately 2000 imported malaria cases annually, necessitating effective surveillance to determine infection sources and...

Deep learning enables rabies virus detection and antibody quantification in cell culture.

Rabies remains a major neglected disease, causing tens of thousands of deaths annually in endemic regions. Cell culture-based assays are central to ra...

Climate variability and COVID-19 non-pharmaceutical interventions shaped dengue transmission in Guangdong: an integrated modeling study.

Dengue fever is a major climate-sensitive mosquito-borne disease shaped by both environmental conditions and human behavior. We quantified the combine...

Predicting abnormal birth weight and identifying associated factors using machine learning in the Hararghe Health and Demographic Surveillance System, Ethiopia.

BACKGROUND: Birth weight is a reliable indicator of intrauterine growth and an important predictor of neonatal survival, growth, and long-term develop...

Approaches to transcatheter aortic valve replacement failure: is more focus on prevention required?

INTRODUCTION: Transcatheter aortic valve replacement (TAVR) has transformed the management of severe aortic stenosis across all surgical risk strata. ...

Big Data-Driven Video Anomaly Detection Using VideoMAE for Visual Analytics in CCTV Surveillance.

In the rapidly evolving industry, the need for surveillance is highly needed for the safety of confidential and highly sensitive organizations. With t...

Deep learning models based on post-procedural angiography for predicting the future risk of in-stent restenosis.

In-stent restenosis (ISR) remains a significant complication after percutaneous coronary intervention. Identifying patients at high risk for ISR from ...