Public Health & Policy

Impact of middle meningeal artery embolization on neurological complications and discharge outcomes in chronic subdural hematoma: A machine learning-based comparative study.

INTRODUCTION: Chronic subdural hematoma (cSDH) predominantly affects older adults, often those with prior head trauma, anticoagulation therapy, or chronic comorbidities. Traditional management involves surgical evacuation; however, middle meningeal artery (MMA) embolization has emerged as a less invasive alternative with the potential for fewer complications. This study compares outcomes of surgic...

Integrating google trends and hybrid statistical-machine learning models for dengue surveillance in an inland vietnamese province: a 94-month evaluation (2013-2021) with search-signal anomaly screening.

Dengue transmission in inland Southeast Asia shows strong seasonality and short-term surges that challenge timely public-health response. We assessed whether province-level Google search activity can support short-horizon dengue monitoring in Dong Nai, Vietnam. Monthly reported dengue cases from July 2013 to April 2021 were aligned with the Google Trends index (GTI) for "Sốt xuất huyết". Models we...

The emerging role of coronary computed tomography for prevention of cardiovascular disease in asymptomatic individuals.

The persistent global rise in atherosclerotic cardiovascular disease (ASCVD) challenges the effectiveness of current risk factor-based algorithms in p...

Review Topic: Don't Cancer Doctors Offer Good-Quality Care?

We offer the perspectives of two veterans on the last quarter century of quality improvement efforts in oncology care. We believe that our colleagues ...

A quarter-century of progress: innovations in lipid medicine that transformed cardiovascular prevention.

This TimeCapsule reviews the major transformations in lipid metabolism and cardiovascular disease prevention during the first quarter of the 21st cent...

Exploration of comorbidity mechanisms between chronic pain and depression: Machine learning prediction models and SHAP interpretability analysis based on the CHARLS cohort.

INTRODUCTION: With rapid population aging in China, depression among middle-aged and older adults has become a major public health concern. Chronic pa...

Reinforcement learning for policymaking in epidemic control: A scoping review.

BACKGROUND: Managing an epidemic demands policies that respond at the pace of the outbreak. Conventional rule‑based interventions struggle to keep up,...

Dynamics of collectivistic language and emotional expression in China's early pandemic: A social media analysis.

Crises can produce contradictory responses in collectivistic cultures, yielding both solidarity and fragmentation. We propose these paradoxes can be u...

First-trimester multi-modal cell-free DNA analysis for prediction of preterm and term preeclampsia.

BACKGROUND: Preeclampsia, which is a leading cause of maternal and perinatal mortality and morbidity, represents a biologically heterogeneous syndrome...

Human-in-the-Loop Governance of Artificial Intelligence in Cardiology: From Ethical Principles to Operational Paradigms.

BACKGROUND: Artificial intelligence (AI) is transforming cardiology across ECG interpretation, imaging, risk prediction, remote monitoring, and workfl...

Improving Precision Diagnosis and Treatment of Diabetes in Low-Resource Settings in Africa Through Structured Clinical Phenotyping: A Narrative Review.

Precision diabetes care is an evolving evidence-based, personalised approach that uses an individual's clinical, metabolic, and genetic data to accura...

Energy-efficient secure routing in wireless sensor networks using fuzzy inference clustering and attention-based multi-scale deep learning.

Wireless Sensor Networks (WSNs) are widely used in applications such as environmental monitoring, smart agriculture, healthcare, industrial automation...

Predicting drilling fluid lost circulation volume and radius using petrophysical well logs and machine learning approaches.

Lost circulation, which refers to the unintended loss of drilling fluid into underground formations, presents a significant challenge in drilling oper...

Microplastics across marine food webs: bioaccumulation, exposome interactions, and emerging oncogenic risks.

Microplastic pollution is a major environmental problem affecting ecosystems, wildlife and people worldwide. Microplastics are solid synthetic polymer...

No-reflow phenomenon during percutaneous coronary intervention: Contemporary insights into mechanisms, prediction, and management.

No-reflow phenomenon remains a common and prognostically adverse complication of percutaneous coronary intervention (PCI), characterized by impaired m...

Chaotic and Stochastic Components in an Influenza Surveillance Series: Nonlinear Dynamics and Predictive Modeling Study.

BACKGROUND: Chaotic dynamics has been the subject of both theoretical and empirical research in epidemiology, with the most recent research strongly f...

The High-resolution Urban Meteorology for Impacts Dataset for Atlanta Metropolitan Region (HUMID-Atlanta).

As urban areas host a large portion of the world's population, high-resolution gridded meteorological data within cities is required to answer impactf...

Development, internal testing, and external validation of an interpretable machine-learning model for predicting imaging-confirmed in-hospital postoperative deep vein thrombosis in older patients with patellar fractures.

BACKGROUND: Older patients with patellar fractures may be at increased risk of postoperative deep vein thrombosis (DVT) because of trauma, perioperati...

Serological surveillance for malaria elimination in Southeast Asia: a scoping review.

BACKGROUND: As Southeast Asian countries advance toward malaria elimination, challenges such as residual transmission reservoirs and zoonotic spill-ov...

Research on influenza surveillance and a prediction model based on multi-source data.

OBJECTIVE: To develop and validate a multivariate Long Short-Term Memory (LSTM) model that integrates multi-source surveillance data for forecasting i...