Researchers at the University of Mississippi are employing machine learning to understand adherence to exercise routines. Their study, analyzing 30,000 surveys, aims to predict whether individuals meet physical activity guidelines by assessing factors like body measurements and demographics. The findings, published in Scientific Reports, underscore the significance of maintaining recommended exercise levels for disease prevention and health improvement. Despite guidelines suggesting 150 minutes of weekly moderate exercise, most Americans fall short, highlighting the need for effective strategies to encourage physical activity adherence.
"Physical activity adherence to the guidelines is a public health concern because of its relationship to disease prevention and overall health patterns," he said.
"We aimed to use machine learning to predict whether people follow physical activity guidelines based on questionnaire data, and find the best combination of variables for accurate predictions," said Choe.
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