Adolescent relational behaviour and the obesity pandemic: A descriptive study applying social network analysis and machine learning techniques.
Pilar Marqués-SánchezMaría Cristina Martínez-FernándezJosé Alberto Benítez-AndradesEnedina Quiroga-SánchezMaría Teresa García-OrdásNatalia Arias-RamosPublished in: PloS one (2023)
Adolescents form subgroups within their classrooms. Subgroup cohesion is defined by the fact that nodes share similarities in aspects that influence obesity, they share attributes related to food quality and gender. The concept of homophily, related to SNA, justifies our results. Artificial intelligence techniques together with the application of the Girvan-Newman provide robustness to the structural analysis of similarities and cohesion between subgroups.
Keyphrases
- artificial intelligence
- machine learning
- network analysis
- young adults
- mental health
- big data
- metabolic syndrome
- insulin resistance
- weight loss
- type diabetes
- deep learning
- high fat diet induced
- weight gain
- sars cov
- coronavirus disease
- healthcare
- physical activity
- clinical trial
- randomized controlled trial
- skeletal muscle
- adipose tissue
- sentinel lymph node
- quality improvement
- early stage
- open label
- risk assessment
- human health
- childhood cancer