Artificial intelligence in globesity research: diagnosis, treatment, and prevention solutions for a healthier world with future recommendations

Farwa Munir (), Hitesh Chopra (), Muhammad Hassan Nasir (), L. V. Simhachalam (), Zainab Bintay Anis (), Shahar Bano (), Nida Islam (), Atif Amin Baig (), Md Belal Bin Heyat (), Saba Parveen (), Mohamed Bahri () and Zia Abbas ()
Additional contact information
Farwa Munir: Lahore General Hospital
Hitesh Chopra: Saveetha Institute of Medical and Technical Sciences
Muhammad Hassan Nasir: Universiti Sultan Zainal Abidin
L. V. Simhachalam: Konaseema Institute of Medical Science and Research Foundation
Zainab Bintay Anis: Semmelweis University
Shahar Bano: University of Management and Technology
Nida Islam: University of Management and Technology
Atif Amin Baig: Management and Science University
Md Belal Bin Heyat: Westlake University
Saba Parveen: Shenzhen University
Mohamed Bahri: Westlake University
Zia Abbas: International Institute of Information Technology

International Journal of System Assurance Engineering and Management, 2025, vol. 16, issue 7, No 6, 2406-2425

Abstract: Abstract Globesity has widely affected the world population. It is a multifactorial health problem. Obesity can be caused by high-fat intake, high-calorie intake, physical inactivity, age, gender, or hormonal issues that can induce many health issues, such as cardiovascular disorders, diabetes, and metabolic disorders. Health facilities are insufficient to provide services to the whole population. In such a case, introducing Artificial Intelligence (AI) in the health sector is one of the most significant steps that can be taken. With the help of AI, the prognosis, diagnosis, and treatment can be provided to individuals within their homes and setups without any physical interactions. Assembling the data collected with AI can help to give more information on the type of obesity prevailing in a particular society so that it could be prevented in the population. Since AI learning is relatively novel within the existing system of medicine, enabling prediction models to be built for medications and examinations that track patients throughout their lifetimes could go a long way toward healthcare delivery. This research brings to the fore information on such personalized AI devices, using machine learning algorithms, which will diagnose the type of obesity and individualized treatment plans. These devices will be more efficient and effective than the current methods, resulting in better obesity control worldwide.

Keywords: Obesity; Medical intelligence; Inflammation; Machine learning; Personalized treatment; AI for medicine; Global health; Deep learning; Medicine (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13198-025-02801-9

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