BACKGROUND: The multifactorial mechanisms driving childhood obesity, a global public health challenge, are yet to be fully elucidated. We aimed to develop and externally validate three widely applied machine learning models alongside logistic regress...
UNLABELLED: Childhood obesity is the main driver of early metabolic risk, predisposing to cardiovascular disease (CVD) and type 2 diabetes (T2D), which cause millions of deaths worldwide. Their progression is influenced by biological, behavioral, and...
BACKGROUND: Adolescent obesity remains a pressing public health challenge, particularly among socioeconomically disadvantaged populations. Artificial intelligence (AI) holds the promise for supporting students in managing daily health behaviors, but ...
Identifying new subgroups among children and adolescents with obesity and metabolic syndrome requires advanced clustering techniques capable of analyzing complex multidimensional data. This study aimed to employ machine learning methods to enhance th...
BACKGROUND: The growing prevalence of obesity in adolescents around the world poses a major threat to public health. This research uses machine learning models to examine the main causes of obesity, in contrast to standard information that typically ...
The purpose of this pilot study was to test an adapted childhood obesity prevention intervention called Preventing Obesity Using Digital-Assisted Movement and Eating (ProudMe) in under-resourced schools. Six schools were cluster-randomized to ProudMe...
Metabolic dysfunction-associated steatotic liver disease (MASLD) in children with obesity correlates with metabolic dysfunction, yet interactions between anthropometrics, liver enzymes, and risk of MASLD remain unclear. This study included 219 childr...
Currently, research has found a close correlation between childhood obesity (CO) and elevated levels of polyamines in the bloodstream. Thus, the identification of key genes associated with polyamines metabolism in CO could offer fresh insights for cl...
Greater than 650 million individuals worldwide are categorized as obese, which is associated with significant health, economic, and social challenges. Given its overlap with leading comorbidities such as heart disease, innovative solutions are necess...
BACKGROUND: Factors underlying the development of childhood underweight, overweight, and obesity are not fully understood. Traditional models have drawbacks in handling large-scale, high-dimensional, and nonlinear data. In this study, we aimed to ide...
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