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Efficacy of Emerging Technologies to Manage Childhood Obesity.
Alotaibi, Mohammad; Alnajjar, Fady; Cappuccio, Massimiliano; Khalid, Sumaya; Alhmiedat, Tareq; Mubin, Omar.
Afiliación
  • Alotaibi M; Faculty of Computers and Information Technology, University of Tabuk, Tabuk, Saudi Arabia.
  • Alnajjar F; College of Information Technology, United Arab Emirates University, Abu Dhabi, United Arab Emirates.
  • Cappuccio M; School of Engineering and IT, University of New South Wales Canberra, Canberra, Australia.
  • Khalid S; College of Information Technology, United Arab Emirates University, Abu Dhabi, United Arab Emirates.
  • Alhmiedat T; Faculty of Computers and Information Technology, University of Tabuk, Tabuk, Saudi Arabia.
  • Mubin O; Industrial Innovation & Robotics Center, University of Tabuk, Tabuk, Saudi Arabia.
Diabetes Metab Syndr Obes ; 15: 1227-1244, 2022.
Article en En | MEDLINE | ID: mdl-35480851
Childhood obesity is a widespread medical condition and presents a formidable challenge for public health. Long-term treatment strategies and early prevention strategies are required because obese children are more likely to carry this condition into adulthood, increasing their risk of developing other major health disorders. The present review analyses various technological interventions available for childhood obesity prevention and treatment. It also examines whether machine learning and technological interventions can play vital roles in its management. Twenty-six studies were shortlisted for the review using various technological strategies and analysed regarding their efficacy. While most of the selected studies showed positive outcomes, there was a lack of studies using robots and artificial intelligence to manage obesity in children. The use of machine learning was observed in various studies, and the integration of social robots and other efficacious strategies may be effective for treating childhood obesity in the future.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Diabetes Metab Syndr Obes Año: 2022 Tipo del documento: Article País de afiliación: Arabia Saudita Pais de publicación: Nueva Zelanda

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Diabetes Metab Syndr Obes Año: 2022 Tipo del documento: Article País de afiliación: Arabia Saudita Pais de publicación: Nueva Zelanda