AIMC Topic: Behavioral Risk Factor Surveillance System

Clear Filters Showing 1 to 6 of 6 articles

[Formula: see text] : explainable attentive transformers for identifying the factors influencing dental visits to enhance dental data completeness.

BMC oral health
BACKGROUND: Access to routine dental care is a cornerstone of preventive healthcare. Regular dental check-ups, which include professional cleanings, examinations, and preventive treatments, play a crucial role in preventing advanced dental diseases s...

AI-driven analysis of diabetes risk determinants in U.S. adults: Exploring disease prevalence and health factors.

PloS one
BACKGROUND: Diabetes remains a major public health concern in the United States, with a complex interplay of behavioral, demographic, and clinical risk factors. This study aims to identify the three best-performing machine learning models for diabete...

Building Risk Prediction Models for Type 2 Diabetes Using Machine Learning Techniques.

Preventing chronic disease
INTRODUCTION: As one of the most prevalent chronic diseases in the United States, diabetes, especially type 2 diabetes, affects the health of millions of people and puts an enormous financial burden on the US economy. We aimed to develop predictive m...

Unhealthy Behaviors, Prevention Measures, and Neighborhood Cardiovascular Health: A Machine Learning Approach.

Journal of public health management and practice : JPHMP
This study identifies and ranks predictors of cardiovascular health at the neighborhood level in the United States. We merged the 500 Cities Data and the 2011-2015 American Community Survey to create a new data set that includes sociodemographic char...