Public Health & Policy

Enhancing MRI Safety: Real-Time Thermal Imaging Integrated with Deep Learning for Burn Prevention

Radiofrequency (RF)-induced burns are the most common MRI-related adverse event. Standard safety practices such as visual checks and patient communication are often insufficient, especially for anesthetized or incapacitated patients. To evaluate the feasibility of combining thermal infrared imaging with a convolutional neural network (CNN) for detecting abnormal heating in real time during MRI. Ph...

The impact of a SmartPhone applicatiOn for skin cancer risk assessmenT on the healthcare system (SPOT-study): A randomized controlled trial

Artificial intelligence (AI)-based mobile health (mHealth) smartphone apps for skin cancer detection are increasingly available to the general population, but their impact on care is unclear. The SPOT study is an investigator-initiated and -designed, unblinded, randomized controlled trial. Participants from a Dutch non-profit health insurance living in and around region Rotterdam the Netherlands, ...

Discrete-Event Simulation Modeling Framework for Cancer Interventions and Population Health in R (DESCIPHR): An Open-Source Pipeline

Simulation models inform health policy decisions by integrating data from multiple sources and forecasting outcomes when there is a lack of comprehens...

RAGCBPNet: An Efficient Feature Fusion Framework for Wearable Cuffless Blood Pressure Monitoring and Long-term Validation in Real-world Settings

Wearable and cuffless blood pressure (BP) monitoring hold great promise for preventive hypertension management, yet few studies have been validated un...

Unintended Pregnancy and Preterm Birth in the United States: Causal Inference and Risk Prediction Using National Survey of Family Growth Data

Unintended pregnancy remains common in high income countries and has been linked to poorer maternal and neonatal outcomes. Whether pregnancy intention...

Development of a Multi-Model Ensemble Tool for Early Prediction of 48-Hour Respiratory Failure Risk in CAP Patients

To develop a predictive tool capable of early identification of the risk of acute respiratory failure within 48 hours of hospital admission in patient...

Evaluating the acceptability, usability and clinical appropriateness of Your Path, an AI-powered tool facilitating relevant access to HIV services post-HIV self-testing in South Africa

Timely linkage to HIV prevention and treatment services following HIV self-testing (HIVST) remains a challenge in many countries. While HIVST offers p...

The Promise and Peril of Large Language Models in Digital Health: GPT-4 Personalizes Cardiovascular Patient Education but Amplifies Gender Biases

Gender-neutral patient education materials often overlook critical sex-based differences in cardiovascular disease (CVD). Large Language Models (LLMs)...

A three-dose MVA-BN mpox vaccination series improves the quality of anti-monkeypox virus immunity

The 2022 global outbreak of clade IIb mpox represented a turning point in public health’s handling of poxviruses. The primary vaccine available for pr...

Prevalence and Predictors of Silent Vertebral Compression Fractures: A Cross-Sectional Population-Based Study Using UK Biobank Imaging Data

To estimate the prevalence of silent vertebral compression fractures (VCF) in an asymptomatic population and to assess the demographic and clinical pr...

Develop and Validate A Fair Machine Learning Model to Indentify Patients with High Care-Continuity in Electronic Health Records Data

Electronic health record (EHR) data often missed care outside a given health system, resulting in data discontinuity. We aimed to: (1) quantify miscla...

Science or Advocacy? The Global Rise of Policy Claims in Population Health Research (1990-2024)

Should original research routinely contain prominent policy claims, such as recommendations for policymakers or broad calls to action? Growing emphasi...

Fairness in infectious disease modeling

The concept of fairness has been extensively examined within the domains of Machine Learning and Artificial Intelligence more broadly. It remains, how...

Epidemiologic Method Review at Scale: Assessing Charlson Comorbidity Versioning Using a Large Language Model

The Charlson Comorbidity Index (CCI) is widely used in epidemiologic studies. However, many versions of the CCI have been developed since the original...

Integrating DHS/MIS Biomarkers with 34 Years of CHIRPS-NDVI Climate Data for Malaria Risk Prediction in Nigeria: A Machine Learning and Spatial Mapping Approach

The estimates of national disease risk are considerably limited by the time of conducted surveys and the geographical inadequacies in surveillance, no...

An Artificial Intelligence Model for Detection of Heart Failure with Preserved Ejection Fraction: A Report from HeartShare Study

Heart failure with preserved ejection fraction (HFpEF) accounts for over half of all heart failure cases in the United States and remains a diagnostic...

Machine learning-driven prediction of opioid and stimulant-related drug overdose fatalities: Analysis of the potential fourth wave

Between 2010 and 2021, fentanyl and stimulants co-involved deaths increased from 0.6% to 32.3% of all overdose deaths in the U.S. The Centers for Dise...

An integrated analytical framework for gender-based violence research: A simulation study combining machine learning and causal inference

Current research on Gender-Based Violence (GBV) typically separates predictive machine learning and causal inference into distinct analytical silos. Y...

Dynamic Stroke Risk Stratification via Machine Learning: A Multi-Level Single-Center Study

Stroke is a leading global public health challenge and the second leading cause of death worldwide. In China, its burden continues to escalate amid po...

Temporal deep learning with clinically engineered biomarkers for the early prediction of type 2 diabetes

Diabetes mellitus remains a major global health burden, causing an estimated 3.4 million deaths in 2024 and highlighting the need for accurate early i...