Technology and Obesity: A Year in Review

Résumé fourni par la source

SMART technological advancements help diagnose, treat, and monitor various diseases at the earliest stages. It presents an opportunity to maintain the key components of conventional obesity management programming while reducing costs and provider time inputs. Various machine learning models have helped predict the risks of obesity and metabolic syndrome. Additionally trained convolutional neural networks can now automatically segment and quantify different adipose tissue compartments. Various multicenter series and randomized clinical trials showed clinically meaningful total and excess weight loss at 6-24 months after minimally invasive robotic bariatric surgical procedures with an acceptable safety profile and shorter recovery compared with surgical sleeve gastrectomy. Virtual reality cue exposure therapy (VR-CET), a Website interactive voice response system, and various mobile applications for tracking diet and activity are the most advanced technological uses in the field of obesity management. The technological advancements should be adaptable, affordable, accessible, accurate, intuitive, sustainable and scalable. The conventional face-to-face interactions in obesity management have yielded short-term dividends, whereas technology-driven methods have the potential to produce long-lasting effects. This narrative review presented the different types of technologies used for obesity management and their outcomes in recent times.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.