AIMC Topic: Pediatric Obesity

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Exploring the effect of the triglyceride-glucose index on bone metabolism in prepubertal children, a retrospective study: insights from traditional methods and machine-learning-based bone remodeling prediction.

PeerJ Jan 1, 2025
BACKGROUND: Childhood obesity poses a significant risk to bone health, but the impact of insulin resistance (IR) on bone metabolism in prepubertal children, as assessed by the triglyceride-glucose (TyG) index, remains underexplored. Bone turnover mar...
Humans Machine Learning Biomarkers Retrospective Studies Female Male Blood Glucose Child Insulin Resistance Pediatric Obesity Triglycerides Bone and Bones Procollagen Bone Remodeling
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An interpretable predictive deep learning platform for pediatric metabolic diseases.

Journal of the American Medical Informatics Association : JAMIA May 20, 2024
OBJECTIVES: Metabolic disease in children is increasing worldwide and predisposes a wide array of chronic comorbid conditions with severe impacts on quality of life. Tools for early detection are needed to promptly intervene to prevent or slow the de...
Humans Electronic Health Records Female Male Deep Learning Adolescent Child, Preschool Child ROC Curve Diabetes Mellitus, Type 2 Pediatric Obesity Metabolic Syndrome Area Under Curve Metabolic Diseases Prediabetic State
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Discovering Pediatric Asthma Phenotypes on the Basis of Response to Controller Medication Using Machine Learning.

Annals of the American Thoracic Society Jan 1, 2018
RATIONALE: Pediatric asthma has variable underlying inflammation and symptom control. Approaches to addressing this heterogeneity, such as clustering methods to find phenotypes and predict outcomes, have been investigated. However, clustering based o...
Humans Machine Learning Algorithms Phenotype Precision Medicine Female Asthma Male Severity of Illness Index Child Treatment Outcome Pediatric Obesity Eosinophils Models, Biological Anti-Asthmatic Agents Bronchodilator Agents
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