A Survey on Machine Learning approach for Early Detection and Prevention of Obesity and Overweight

A Survey on Machine Learning approach for Early Detection and Prevention of Obesity and Overweight
Author(s):
Prof. M.K. Nivangune, Simran Sayyad, Mrunal Shewale, Prachi Rane, Prerana Madhavi
Keywords:
Obesity; Overweight; Prediction; Prevention; Web application; Machine Learning.
Abstract
Obesity is a major global epidemic, impacting over 2.1 billion people, with 41% of the world's population projected to be overweight or obese by 2030. This issue poses serious health risks, including diabetes and heart problems. To tackle this crisis, a comprehensive dataset has been created using data from educational institutions, focusing on Body Mass Index (BMI) as an indicator. Early detection is crucial for intervention, including lifestyle changes. A framework has been designed to forecast BMI and body fat percentage, as well as to provide personalized preventative strategies. Real time detection is also inculcated for determining whether the person is obese or not. The program is based on data collected from schools and colleges to create effective models for obesity detection and prevention. The results are compiled and shown on a web application that also contains numerous preventative measures and calculators.
Article Details
Unique Paper ID: 161862 Publication Volume & Issue: Volume 10, Issue 6 Page(s): 370 - 375
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