Objective To determine how machine learning has been applied to prediction applications in
population health contexts. Specifically, to describe which outcomes have been studied, the …

The field of nutritional epidemiology faces challenges posed by measurement error, diet as
a complex exposure, and residual confounding. The objective of this perspective article is to …

Cardiovascular disease (CVD) is the leading cause of death worldwide and a major public
health concern. CVD prediction is one of the most effective measures for CVD control. In this …

Background Approximately 10% to 20% of people with concussion experience prolonged
post-concussion symptoms (PPCS). There is limited information identifying risk factors for …

Background Our objective was to determine the impacts of artificial intelligence (AI) on
public health practice. Methods We used a fundamental qualitative descriptive study design …

Objective: Child undernutrition is a global public health problem with serious implications. In
this study, we estimate predictive algorithms for the determinants of childhood stunting by …

Background: More than one million people acquire sexually transmitted infections (STIs)
every day globally. It is possible that predicting an individual's future risk of HIV/STIs could …

Background Little is known about the role of emerging plant-based dietary patterns in
cardiovascular disease (CVD) risk at the national population level. Objectives The objectives …

Abstract Purpose of Review Current risk prediction tools do not include physical activity (PA)
or cardiorespiratory fitness (CRF), despite their robust association with adverse …

Importance Predicting chronic disease incidence for the population provides a
comprehensive picture to health policy makers of their jurisdictions' overall future chronic …