Public Health & Policy

ListPred: A predictive ML tool for virulence potential and disinfectant tolerance in Listeria monocytogenes.

Despite current surveillance and sanitation strategies, foodborne pathogens continue to threaten the food industry and public health. Whole genome sequencing (WGS) has reached an unprecedented resolution to analyse and compare pathogenic bacterial isolates. The increased resolution significantly enhances the possibility of tracing transmission routes and contamination sources of foodborne pathogen...

Tlalpan 2020 Case Study: Enhancing Uric Acid Level Prediction with Machine Learning Regression and Cross-Feature Selection.

Uric acid is a key metabolic byproduct of purine degradation and plays a dual role in human health. At physiological levels, it acts as an antioxidant, protecting against oxidative stress. However, excessive uric acid can lead to hyperuricemia, contributing to conditions like gout, kidney stones, and cardiovascular diseases. Emerging evidence also links elevated uric acid levels with metabolic di...

Machine learning-based prediction models for renal impairment in Chinese adults with hyperuricaemia: risk factor analysis.

In hyperuricaemic populations, multiple factors may contribute to impaired renal function. This study aimed to establish a machine learning-based mode...

How to leverage large language models for automatic ICD coding.

ICD coding, which involves assigning appropriate ICD codes to clinical notes, is essential for healthcare tasks such as health expense claims, insuran...

Enhanced personalized prediction of baseball-related upper extremity injuries through novel features and explainable artificial intelligence.

Upper extremity injuries in baseball players demand advanced prevention. Our study analyzed clinical features using machine learning techniques to pro...

Evaluation of factors associated with adult skeletal fluorosis in coal-burning type of endemic fluorosis and initial screening model based on machine learning in Guizhou, Southwest China.

Skeletal fluorosis caused by coal-burning type endemic fluorosis greatly affects the health of the population in the affected areas, but large-scale d...

Forecasting trends of rising emergency department chest imaging using machine learning.

INTRODUCTION: Imaging studies in the acute care setting, such as the emergency room, have been increasing. In this report, we use the Centers for Medi...

An ultra-sensitive, intelligent platform for food safety monitoring: Label-free detection of illegal additives using self-assembled SERS substrates and machine learning.

To overcome the limitations of SERS in food safety monitoring, particularly significant interference from citrate ions, this study introduces an intel...

Epidemiology and risk factors of Clonorchis sinensis infection in the mountainous areas of Longsheng County, Guangxi: insights from automated machine learning.

Clonorchis sinensis (C. sinensis) is mainly prevalent in Northeast and South China, with Guangxi being the most severely affected region. This study a...

Efficacy and Safety of a Medical Robot for Non-Face-to-Face Nasopharyngeal Swab Specimen Collection: Nonclinical and Clinical Trial Findings for COVID-19 Testing.

ObjectivesTo meet the high demand for polymerase chain reaction (PCR) tests to diagnose COVID-19 and rapidly control the outbreak, an efficient and sa...

CEL: A Continual Learning Model for Disease Outbreak Prediction by Leveraging Domain Adaptation via Elastic Weight Consolidation.

Continual learning is the ability of a model to learn over time without forgetting previous knowledge. Therefore, adapting new data in dynamic fields ...

Artificial intelligence in public health: promises, challenges, and an agenda for policy makers and public health institutions.

Artificial intelligence (AI) can rapidly analyse large and complex datasets, extract tailored recommendations, support decision making, and improve th...

A Scoping Review of Artificial Intelligence for Precision Nutrition.

With the role of artificial intelligence (AI) in precision nutrition rapidly expanding, a scoping review on recent studies and potential future direct...

Enhancing Slip, Trip, and Fall Prevention: Real-World Near-Fall Detection with Advanced Machine Learning Technique.

Slips, trips, and falls (STFs) are a major occupational hazard that contributes significantly to workplace injuries and the associated financial costs...

Contribution of Structure Learning Algorithms in Social Epidemiology: Application to Real-World Data.

Epidemiologists often handle large datasets with numerous variables and are currently seeing a growing wealth of techniques for data analysis, such as...

Machine Learning Predicts Bleeding Risk in Atrial Fibrillation Patients on Direct Oral Anticoagulant.

Predicting major bleeding in nonvalvular atrial fibrillation (AF) patients on direct oral anticoagulants (DOACs) is crucial for personalized care. Alt...

Urban and rural disparities in stroke prediction using machine learning among Chinese older adults.

Stroke is a significant health concern in China. Differences in stroke risk between rural and urban areas have been highlighted in prior research. How...

Study on the prediction performance of AIDS monthly incidence in Xinjiang based on time series and deep learning models.

OBJECTIVE: AIDS is a highly fatal infectious disease of Class B, and Xinjiang is a high-incidence region for AIDS in China. The core of prevention and...

Association of High-Deductible Health Plans and Complicated Appendicitis Among Children.

OBJECTIVE: To determine whether high-deductible health plans (HDHPs) are associated with complicated disease and hospitalization costs for children wi...

Validation of a machine learning model for indirect screening of suicidal ideation in the general population.

Suicide is among the leading causes of death worldwide and a concerning public health problem, accounting for over 700,000 registered deaths worldwide...