Engineering Professor Outlines Artificial Intelligence to Detect Risk of Obesity
Obesity disease is a significant health issue that has affected millions of people worldwide. A new study co-authored by Dr. Manjeet Rege, a professor in the School of Engineering at the University of St. Thomas, explores the application of ensemble learning techniques in predicting obesity risk using lifestyle data.
Manjeet Rege
“By leveraging advanced algorithms in machine learning and artificial intelligence, it becomes feasible to build models capable of identifying individuals at risk of developing obesity,” said Rege, who is also director of Center for Applied Artificial Intelligence at St. Thomas. “We hope this research contributes to the development of more effective obesity prevention and intervention strategies.”
The findings are in a new research paper titled, “An investigation of ensemble learning techniques for obesity risk prediction using lifestyle data,” which has been published in the Decision Analytics Journal, Elsevier.
In the health care sector, online medical repositories and hospitals are generating vast amounts of data, thereby providing valuable resources for researchers to explore and harness AI techniques to address real-life health issues, the research found.
Identifying underlying reasons for the onset of obesity risk in its early stage has become challenging for medical practitioners. The growing volume of lifestyle data related to obesity has made it imperative to employ effective machine-learning algorithms that can gather insights from the underlying data trends and identify critical patient conditions.
The perfect climate for obesity to flourish has been created by traditional diets heavy in processed foods and low in physical exercise as technology develops and urbanization picks up speed. The resultant effects include an increase in disorders linked to obesity, such as diabetes, heart problems, and other ailments. Early detection of diseases and identification of associated risks can serve as crucial motivators for patients, encouraging them to make positive changes in their dietary habits, lifestyles, and exercise routines.
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