Public Health & Policy

Using Natural Language Processing to develop risk-tier specific suicide prediction models for Veterans Affairs patients.

Suicide is a leading cause of death. Suicide rates are particularly elevated among Department of Veterans Affairs (VA) patients. While VA has made impactful suicide prevention advances, efforts primarily target high-risk patients with documented suicide risk. This high-risk population accounts for less than 10% of VA patient suicide deaths. We previously evaluated epidemiological patterns among VA...

Identifying biological markers and sociodemographic factors that influence the gap between phenotypic and chronological ages.

INTRODUCTION: The world's population is aging rapidly, leading to increased public health and economic burdens due to age-related cardiovascular and neurodegenerative diseases. Early risk detection is essential for prevention and to improve the quality of life in elderly individuals. Plus, health risks associated with aging are not directly tied to chronological age, but are also influenced by a c...

Self-monitoring of Oral Health Using Smartphone Selfie Powered by Artificial Intelligence: Implications for Preventive Dentistry.

PURPOSE: With the increasing use of artificial intelligence (AI) in dentistry, it is feasible to self-monitor oral health using Oral Health AI Advisor...

Text mining of verbal autopsy narratives to extract mortality causes and most prevalent diseases using natural language processing.

Verbal autopsy (VA) narratives play a crucial role in understanding and documenting the causes of mortality, especially in regions lacking robust medi...

Enhancing shipboard oil pollution prevention: Machine learning innovations in oil discharge monitoring equipment.

Maritime operations face significant challenges in environmental stewardship, particularly in managing oil discharges from tankers as mandated by the ...

Economic Evaluation of a Novel Lung Cancer Diagnostic in a Population of Patients with a Positive Low-Dose Computed Tomography Result.

Early detection of lung cancer is crucial for improving patient outcomes. Although advances in diagnostic technologies have significantly enhanced th...

An automated framework for pediatric hip surveillance and severity assessment using radiographs.

PURPOSE: Hip dysplasia is the second most common orthopedic condition in children with cerebral palsy (CP) and may result in disability and pain. The ...

Predicting structure-targeted food bioactive compounds for middle-aged and elderly Asians with myocardial infarction: insights from genetic variations and bioinformatics-integrated deep learning analysis.

Myocardial infarction (MI) is a significant global health issue. Despite the advances in genome-wide association studies, a complete genetic and molec...

Deep feature fusion with computer vision driven fall detection approach for enhanced assisted living safety.

Assisted living facilities cater to the demands of the elderly population, providing assistance and support with day-to-day activities. Fall detection...

Perceived Usefulness of Robotic Technology for Patient Fall Prevention.

BACKGROUND: Technology has the potential to prevent patient falls in healthcare settings and to reduce work-related injuries among healthcare provider...

Using AI to Differentiate Mpox From Common Skin Lesions in a Sexual Health Clinic: Algorithm Development and Validation Study.

BACKGROUND: The 2022 global outbreak of mpox has significantly impacted health facilities, and necessitated additional infection prevention and contro...

Geospatial and Temporal Analysis of Avian Influenza Risk in Thailand: A GIS-Based Multi-Criteria Decision Analysis Approach for Enhanced Surveillance and Control.

Avian influenza (AI) is a viral infection that profoundly affects global poultry production. This study aimed to identify the spatial and temporal fac...

Effects of School Violence Prevention Education Using a Chatbot (SVPE-C) on Sixth-Grade Students in South Korea.

This study investigated the effects of school violence prevention education using a chatbot (SVPE-C) on sixth-grade students. By applying a pre and po...

Innovation in public health surveillance for social distancing during the COVID-19 pandemic: A deep learning and object detection based novel approach.

The Corona Virus Disease (COVID-19) has a huge impact on all of humanity, and people's disregard for COVID-19 regulations has sped up the disease's sp...

Machine learning to attribute the source of Campylobacter infections in the United States: A retrospective analysis of national surveillance data.

OBJECTIVES: Integrating pathogen genomic surveillance with bioinformatics can enhance public health responses by identifying risk and guiding interven...

Prediction of cognitive impairment among Medicare beneficiaries using a machine learning approach.

OBJECTIVE: Developing machine learning (ML) models to predict cognitive impairment among Medicare beneficiaries in the United States.

A Physics-Informed Neural Network approach for compartmental epidemiological models.

Compartmental models provide simple and efficient tools to analyze the relevant transmission processes during an outbreak, to produce short-term forec...

Trustworthy and ethical AI-enabled cardiovascular care: a rapid review.

BACKGROUND: Artificial intelligence (AI) is increasingly used for prevention, diagnosis, monitoring, and treatment of cardiovascular diseases. Despite...

Volume Measurements for Surveillance after Endovascular Aneurysm Repair using Artificial Intelligence.

OBJECTIVE: Surveillance after endovascular aneurysm repair (EVAR) is suboptimal due to limited compliance and relatively large variability in measurem...

Prostate cancer treatment recommendation study based on machine learning and SHAP interpreter.

This study utilized data from 140,294 prostate cancer cases from the Surveillance, Epidemiology, and End Results (SEER) database. Here, 10 different m...