Public Health & Policy

Latest AI and machine learning research in public health & policy for healthcare professionals.

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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....

How to leverage large language models for automatic ICD coding.

ICD coding, which involves assigning appropriate ICD codes to clinical notes, is essential for healt...

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...

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 incre...

Popfinder: A Highly Effective Artificial Neural Network Package for Genetic Population Assignment.

The ability to assign biological samples to source populations with high accuracy and precision base...

Comparison of Machine Learning Algorithms Identifying Children at Increased Risk of Out-of-Home Placement: Development and Practical Considerations.

OBJECTIVE: To develop a machine learning (ML) algorithm capable of identifying children at risk of o...

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 knowledg...

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 recomm...

A Scoping Review of Artificial Intelligence for Precision Nutrition.

With the role of artificial intelligence (AI) in precision nutrition rapidly expanding, a scoping re...

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 growi...

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 wor...

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 anticoagul...

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 re...

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 ...

Reporting Quality of AI Intervention in Randomized Controlled Trials in Primary Care: Systematic Review and Meta-Epidemiological Study.

BACKGROUND: The surge in artificial intelligence (AI) interventions in primary care trials lacks a s...

Machine learning-based prediction model for patients with recurrent Staphylococcus aureus bacteremia.

BACKGROUND: Staphylococcus aureus bacteremia (SAB) remains a significant contributor to both communi...

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, accou...

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