Obesity and the role of artificial intelligence as a prediction tool

Abstract

Obesity is one of the leading public health challenges worldwide, with a growing prevalence and a strong association with chronic noncommunicable diseases. Traditional methods for risk assessment and clinical management have shown limitations in addressing the multifactorial complexity of this condition. In this context, artificial intelligence (AI) emerges as an innovative tool capable of enhancing risk prediction and optimizing treatment strategies. This article reviews current AI approaches applied to obesity, ranging from predictive models based on clinical, genomic, and behavioural data to personalized digital interventions in nutrition, physical activity, and therapeutic adherence. Furthermore, the main advantages, limitations, and ethical challenges of clinical implementation are analyzed. Finally, recommendations are provided to guide the responsible integration of AI into medical practice, aiming to advance toward more predictive, preventive, and personalized medicine in obesity management.

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