A Concise Review on Identifying Obesity Early: Leveraging AI and ML Targeted Advantage
Keywords:
Chronic disease, prevention, personalized coaching, health management, clinical decision making, machine learning.Abstract
The pervasive nature of obesity has escalated into a global epidemic, posing a significant threat that could overwhelm healthcare systems, economies, and societal well-being. Given its strong association with debilitating chronic conditions, such as cardiovascular disease, there's an urgent need for more effective strategies to predict, prevent, and manage this complex health challenge. This review aims to explore how Artificial Intelligence (AI) and Machine Learning (ML) can be leveraged as powerful tools to enhance the early identification, proactive prevention, and improved management of obesity. Our objective is to highlight AI's potential in developing more precise and effective measures to combat this worldwide health crisis. The present review study explores the possibility of applying AI and ML in the care and prevention of pediatric obesity. The study discussed diversity of obesity causes citing genetic susceptibility, environmental driving and lifestyle preferences and emphasize the drawbacks of the customary methods of detection and treatment. The study review AI and ML models that have been used to predict the occurrence of obesity with emphasis on when the children will be very early to prevent obesity health effects. The study also reviews the implementation of AI-based trends in obesity care and compare its usage between healthcare specialists and patients. In addition, clinical practice, AI combines information in electronic health records, wearables, and health-tracking app to make person-centered treatment and evidence-based decisions possible. Furthermore, to patients, AI-based services provide them with individual coaching, motivation and long-term behavioral change due to constant monitoring and feedback. Lastly important issues such as data privacy, healthcare disparities, and social determinants of health that affect the effective implementation of AI to treat obesity, and provide suggestions on the potential research and policies to improve equity in the future.
Downloads
Published
Issue
Section
License
Authors retain copyright and grant the journal the right of first publication. Articles published in this journal are licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), permitting unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to Cite
Similar Articles
- Ngwu Comfort, Advances in Machine Learning Approaches for Predicting Aqueous Solubility in Drug Discovery , Applied Science, Computing, and Energy: Vol. 2 No. 1 (2025): VOLUME 2 ISSUE 1
- Mu’awiya Baba Aminu, Khaurat Kadiri, Ayobami Oni, Rabi Elabor, Machine Learning–Driven Remote Sensing Framework for Predicting Groundwater Pollution under Climate Change Scenarios , Applied Science, Computing, and Energy: Vol. 4 No. 2 (2026): Volume 4 Issue 2
- Amarachi Nelly Charles, Oluwabukola Victoria Akinyemi, Chinyan Blessing, AI-Enabled Marketing Communication and Machine Learning Analytics for Consumer Insights, Brand Positioning, and Business Growth , Applied Science, Computing, and Energy: Vol. 1 No. 1 (2024): VOLUME 1 ISSUE 1
- Edoise Areghan , Osondu Onwuegbuchi, Predictive Cyber Threat Analysis in Cloud Platforms Using Artificial Intelligence and Machine Learning Algorithms , Applied Science, Computing, and Energy: Vol. 1 No. 1 (2024): VOLUME 1 ISSUE 1
- Moses Oluwasegun Odewale, Moses Olagoke Odejobi, Olanrewaju Oluwaseun Ajayi, AI-Driven Self-Optimizing Framework for Real-Time Wireless Network Performance Enhancement , Applied Science, Computing, and Energy: Vol. 1 No. 1 (2024): VOLUME 1 ISSUE 1
- Aman Shrestha, A Strategic Framework for Strengthening Cyber Risk Governance and Resilience in US Critical Infrastructure Sectors , Applied Science, Computing, and Energy: Vol. 3 No. 3 (2025): Volume 3, Issue 3
- Ololade Serifat Omosunlade, Evidence-Based Autism-Responsive Curriculum for Emotional Regulation and Career Readiness , Applied Science, Computing, and Energy: Vol. 3 No. 2 (2025): VOLUME 3 ISSUE 2
- Mu’awiya Baba Aminu, Sangodiji Enoch Ezekiel, Daniel Chukwunonso Chukwudi, Anako Shefawu Onize, Changde A. Nanfa, Saleh Mamman Abdullahi, Review of Carbon Capture and Storage (CCS) and the Way Forward in Developing Country – Nigeria , Applied Science, Computing, and Energy: Vol. 2 No. 2 (2025): VOLUME 2 ISSUE 2
- Changde A. Nanfa, Christopher Simon Dalom, Olaitan Gbolahan Olaseni, Mu’awiya Baba Aminu, Okiyi I. Millicent, Geoelectrical Investigation of Aquifer Systems in Toro and Environs, Northeast Nigeria , Applied Science, Computing, and Energy: Vol. 3 No. 1 (2025): VOLUME 3 ISSUE 1
- Silas Abahia Ihedioha, Bright Okore Osu, Samuel Chidiebere Ani, Modeling Urban Heat Island Dynamics Using Fractional Calculus: A Comparative Study with Classical Heat Diffusion Models , Applied Science, Computing, and Energy: Vol. 4 No. 1 (2026): Volume 4 Issue 1
You may also start an advanced similarity search for this article.