[HTML][HTML] Machine learning models to predict childhood and adolescent obesity: a review

G Colmenarejo - Nutrients, 2020‏ - mdpi.com
The prevalence of childhood and adolescence overweight an obesity is raising at an
alarming rate in many countries. This poses a serious threat to the current and near-future …

A survey on machine and deep learning models for childhood and adolescent obesity

H Siddiqui, A Rattani, NK Woods, L Cure… - IEEE …, 2021‏ - ieeexplore.ieee.org
Childhood and adolescent obesity is a serious health problem that is on the rise at the
global level. Earlier, certain diseases such as Type 2 diabetes, high blood pressure, and …

Predicting obesity in adults using machine learning techniques: an analysis of Indonesian basic health research 2018

SA Thamrin, DS Arsyad, H Kuswanto, A Lawi… - Frontiers in …, 2021‏ - frontiersin.org
Obesity is strongly associated with multiple risk factors. It is significantly contributing to an
increased risk of chronic disease morbidity and mortality worldwide. There are various …

Machine learning techniques for prediction of early childhood obesity

TM Dugan, S Mukhopadhyay, A Carroll… - Applied clinical …, 2015‏ - thieme-connect.com
Objectives: This paper aims to predict childhood obesity after age two, using only data
collected prior to the second birthday by a clinical decision support system called CHICA …

Machine learning approach for the early prediction of the risk of overweight and obesity in young people

B Singh, H Tawfik - Computational Science–ICCS 2020: 20th International …, 2020‏ - Springer
Obesity is a major global concern with more than 2.1 billion people overweight or obese
worldwide which amounts to almost 30% of the global population. If the current trend …

A survey on data mining techniques used in medicine

SM Birjandi, SH Khasteh - Journal of diabetes & metabolic disorders, 2021‏ - Springer
Data mining is the process of analyzing a massive amount of data to identify meaningful
patterns and detect relations, which can lead to future trend prediction and appropriate …

[PDF][PDF] Op-RMSprop (optimized-root mean square propagation) classification for prediction of polycystic ovary syndrome (PCOS) using hybrid machine learning …

KP Rakshitha, NC Naveen - International Journal of Advanced …, 2022‏ - researchgate.net
Polycystic Ovary Syndrome is a common women's health problem caused by the imbalance
in the reproductive hormones which causes problems in the ovaries. An appropriate …

A machine learning approach for predicting weight gain risks in young adults

B Singh, H Tawfik - 2019 10th International Conference on …, 2019‏ - ieeexplore.ieee.org
Individuals develo** signs of weight gain or obesity are at a risk of develo** serious
illnesses such as type 2 diabetes, respiratory problems, coronary heart disease and stroke …

Application of machine learning techniques to predict teenage obesity using earlier childhood measurements from millennium cohort study

B Singh, A Gorbenko, A Palczewska… - Proceedings of the 2023 …, 2023‏ - dl.acm.org
Obesity is a major global concern with more than 2.1 billion people overweight or obese
worldwide, which amounts to almost 30% of the global population. If the current trend …

[PDF][PDF] Conceptual Framework Based On Type-2 Fuzzy Logic Theory for Predicting Childhood Obesity Risk.

K Almohammadi - International Journal of Online & Biomedical …, 2020‏ - researchgate.net
Obesity is a critical public health concern affecting a wide range of people globally. The rise
in obesity is limited to not only the wealthiest countries but also the poorest. Childhood …