The problem of estimation and forecasting of obesity prevalence using sparsely collected data-Reference-Cited by-同舟云学术

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The problem of estimation and forecasting of obesity prevalence using sparsely collected data

Published:2024-06 Issue: Volume:132 Page:107860
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Rojo-González Luis^ORCID,Dunstan Jocelyn,Cuadrado Cristóbal,Ávalos Denisse,Moraga-Correa Javier,Troncoso Nelson,Vásquez Óscar C.^ORCID

Publisher

Elsevier BV

Reference58 articles.

1. A review of uncertainty quantification in deep learning: Techniques, applications and challenges;Abdar;Inf. Fusion,2021

2. Minos for AMPL;AMPL Team,2021

3. Obesity: definition, comorbidities, causes, and burden;Apovian;Am. J. Managed Care,2016

4. Modelamiento Dinámico del Índice de Masa Corporal de la Población en Chile;Ávalos,2015

5. Mathematical model for estimating nutritional status of the population with poor data quality in developing countries: The case of Chile;Ávalos,2021

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