Public Health & Policy

Machine learning for predicting institutionalization and mortality risks among older home care recipients with routinely collected need assessment data: explainable AI for long-term care.

BACKGROUND: Identifying older home care recipients at risk of institutionalization in advance is crucial for providing preventive services. Supporting the decision-making of care workers in prioritizing their limited resources would be useful for promoting an aging-in-place policy. OBJECTIVE: This study aims to develop and interpret explainable machine learning (ML) methods for predicting institut...

Heterogeneous income gradients in early motherhood in Mexico: a population-based multi-method study, 2000-2020.

BACKGROUND: Early motherhood remains a major public health and equity challenge in low- and middle-income countries, especially in Latin America. While poverty, education, gender norms, and barriers to sexual and reproductive health are well-established determinants, how household income translates into (or fails to translate into) delayed childbearing remains insufficiently understood-particularl...

Cardiac substructure dosimetry in thoracic radiotherapy: moving beyond mean heart dose and toward precision cardiac risk mitigation.

BACKGROUND: Radiation-induced heart disease (RIHD) remains a clinically significant consequence of thoracic radiotherapy (RT). Historically, the mean ...

Predictive Modeling of Enterovirus Hospital Burden Using Machine Learning and Age-Specific Surveillance Data: Operational Forecasting in Taiwan During the Postpandemic Era.

BACKGROUND: Enterovirus infections cause substantial pediatric morbidity worldwide, with severe cases requiring hospitalization. Accurate forecasting ...

Advances in the management of pediatric low-grade glioma.

Pediatric low-grade gliomas (pLGGs), the most common CNS tumors in children, are increasingly recognized as chronic diseases with prolonged courses an...

Impact of meteorological factors on other infectious diarrhea in mainland China: comprehensive risk assessment, forecasting and early warning.

Other infectious diarrhea (OID) is a major public health burden in China and a typical weather-sensitive disease, yet nationwide evidence that links c...

Stochastic Expansion of Radionuclide Inhalation Dosimetry for Consequence Management Application: Uncertainty and Sensitivity Analysis in the ICRP 130 Human Respiratory Tract Model.

Releases from nuclear or radiological security events can result in significant internal radiation contamination through inhalation of particulate con...

Patient and Facility Factors Associated with Uptake of NTAP-Billed AI to Identify Suspected LVO in Ischemic Stroke.

PURPOSE: Medicare's New Technology Add-On Payment (NTAP) incentivizes the adoption of innovative technologies. We examined factors associated with the...

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 underly...

Forecasting monthly hepatitis B cases in China: a nationwide comparative study based on surveillance data.

BACKGROUND: Robust forecasting of hepatitis B trends is important for long-term surveillance and public health planning in China. However, evidence re...

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...

Precision Nutrition and Chronic Disease: Integrating Genomics, Microbiome, and Digital Health for Personalized Dietary Interventions.

Chronic non-communicable diseases (NCDs), including cardiovascular disease, type 2 diabetes, obesity, and metabolic syndrome, account for more than 70...

Predicting High-Risk Colorectal Polyps in African Americans Using Pre-colonoscopy Clinical Features: Machine Learning Model Development and Temporal Validation.

PURPOSE: Risk stratification for advanced colorectal polyps typically relies on colonoscopy and/or pathology findings. However, there is growing inter...

Artificial intelligence in pediatric endoscopy for hereditary polyposis syndromes: promises and challenges.

PURPOSE OF REVIEW: Children with hereditary polyposis syndromes require long-term endoscopic surveillance to reduce risks of gastrointestinal complica...

Comparative 10-year performance of mammography artificial intelligence, polygenic, and clinical breast cancer risk models in the Kaiser Permanente Research Bank.

BACKGROUND: We compared performance across 3 breast cancer risk domains-clinical, polygenic, and mammography artificial intelligence-alone and in comb...

Machine learning based prediction models for first stroke in community primary care: a systematic review and meta-analysis.

BACKGROUND: Stroke is the third leading cause of death and the fourth leading cause of disability globally, particularly in low- and middle-income cou...

Super learner model for predicting carotid plaque regression in type 2 diabetes on PCSK9 inhibitors.

OBJECTIVES: Evidence regarding the effects of proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors on carotid plaque regression in patient...

Biomechanical phenotypes of 90° change of direction in football players: Unsupervised machine learning in anterior cruciate ligament injury prevention.

PURPOSE: Neuromuscular and biomechanical deficits contribute to anterior cruciate ligament (ACL) injury risk in football. Artificial intelligence (AI)...

Dual-Recognition AIEgens-Lysozyme Assemblies for Interpretable Machine Learning-Enabled Sensor Arrays: Toward Rapid and Transparent Surveillance of Microbial Threats.

Array-based sensing technology holds immense potential for the rapid identification of pathogenic bacteria. Nevertheless, developing a universal strat...

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...