Teke, Jennifer, Msiska, Maines, Adanini, Oluronke Abisoye, Egbon, Eghosasere, Osborne, Augustus and Olawade, David ORCID: https://orcid.org/0000-0003-0188-9836 (2025) Artificial intelligence for obesity management: A review of applications, opportunities, and challenges. Obesity Medicine, 58. p. 100657.

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Abstract

Traditional obesity management approaches, including dietary interventions, physical activity programmes, pharmacotherapy, and behavioural therapies, face significant limitations in scalability, personalisation, and long-term adherence rates. The emergence of artificial intelligence (AI) technologies, particularly machine learning and deep learning algorithms, has opened new frontiers for transforming obesity prevention, diagnosis, and management strategies. This comprehensive narrative review synthesises current evidence on AI applications in obesity management, examining technological innovations from predictive risk models to personalised digital therapeutics. The review explores AI-based diagnostic tools utilising computer vision for body composition analysis, predictive algorithms identifying high-risk individuals using electronic health records, personalised behavioural interventions powered by reinforcement learning, and remote monitoring systems integrating wearable technologies with intelligent data analytics. Furthermore, it investigates clinical effectiveness of AI-driven digital therapeutics platforms and examines AI integration within clinical decision support systems. The analysis reveals significant benefits including enhanced scalability for population-level interventions, improved personalisation through real-time data integration, increased precision in risk stratification, and potential cost-effectiveness through optimised resource allocation. However, substantial challenges remain, including data privacy and security concerns, algorithmic bias that may exacerbate health disparities, limited large-scale clinical validation, declining user engagement over time, and complex regulatory and ethical considerations. Addressing these challenges through multidisciplinary collaboration, robust validation studies, and ethical frameworks will be critical for successfully integrating AI technologies into routine obesity care and achieving equitable health outcomes across diverse populations.

Item Type:	Article
Status:	Published
DOI:	10.1016/j.obmed.2025.100657
School/Department:	London Campus
URI:	https://ray.yorksj.ac.uk/id/eprint/13192

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