Efficacy of Emerging Technologies to Manage Childhood Obesity.
Mohammad AlotaibiFady S AlnajjarMassimiliano CappuccioSumaya KhalidTareq AlhmiedatOmar MubinPublished in: Diabetes, metabolic syndrome and obesity : targets and therapy (2022)
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.
Keyphrases
- machine learning
- artificial intelligence
- public health
- healthcare
- case control
- big data
- deep learning
- metabolic syndrome
- young adults
- type diabetes
- weight loss
- physical activity
- mental health
- insulin resistance
- body mass index
- health information
- weight gain
- risk assessment
- climate change
- combination therapy
- obese patients