Author
Listed:
- 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)
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.
Suggested Citation
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 & Zia Abbas, 2025.
"Artificial intelligence in globesity research: diagnosis, treatment, and prevention solutions for a healthier world with future recommendations,"
International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 16(7), pages 2406-2425, July.
Handle:
RePEc:spr:ijsaem:v:16:y:2025:i:7:d:10.1007_s13198-025-02801-9
DOI: 10.1007/s13198-025-02801-9
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