AIMC Topic: Overweight
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Factors associated with underweight, overweight, and obesity in Chinese children aged 3-14 years using ensemble learning algorithms.
Journal of global health
Feb 7, 2025
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...
Multimodal machine learning for analysing multifactorial causes of disease-The case of childhood overweight and obesity in Mexico.
Frontiers in public health
Jan 7, 2025
BACKGROUND: Mexico has one of the highest global incidences of paediatric overweight and obesity. Public health interventions have shown only moderate success, possibly from relying on knowledge extracted using limited types of statistical data analy...
Interpretable machine learning for identifying overweight and obesity risk factors of older adults in China.
Geriatric nursing (New York, N.Y.)
Jan 4, 2025
OBJECTIVE: To estimate the importance of risk factors on overweight/obesity among older adults by comparing different predictive model.
Using interpretable machine learning methods to identify the relative importance of lifestyle factors for overweight and obesity in adults: pooled evidence from CHNS and NHANES.
BMC public health
Nov 1, 2024
BACKGROUND: Overweight and obesity pose a huge burden on individuals and society. While the relationship between lifestyle factors and overweight and obesity is well-established, the relative contribution of specific lifestyle factors remains unclear...
Robust identification key predictors of short- and long-term weight status in children and adolescents by machine learning.
Frontiers in public health
Sep 24, 2024
BACKGROUND: Early identification of high-risk individuals for weight problems in children and adolescents is crucial for implementing timely preventive measures. While machine learning (ML) techniques have shown promise in addressing this complex cha...
Identification of Psychological Treatment Dropout Predictors Using Machine Learning Models on Italian Patients Living with Overweight and Obesity Ineligible for Bariatric Surgery.
Nutrients
Aug 8, 2024
According to the main international guidelines, patients with obesity and psychiatric/psychological disorders who cannot be addressed to surgery are recommended to follow a nutritional approach and a psychological treatment. A total of 94 patients (T...
Predicting the onset of overweight in Chinese high school students: a machine-learning approach in a one-year prospective cohort study.
Endocrine
Jun 10, 2024
OBJECTIVE: This study aimed to develop and evaluate machine-learning models for predicting the onset of overweight in adolescents aged 14‒17, utilizing easily collectible personal information.
Automated abdominal adipose tissue segmentation and volume quantification on longitudinal MRI using 3D convolutional neural networks with multi-contrast inputs.
Magma (New York, N.Y.)
Feb 1, 2024
OBJECTIVE: Increased subcutaneous and visceral adipose tissue (SAT/VAT) volume is associated with risk for cardiometabolic diseases. This work aimed to develop and evaluate automated abdominal SAT/VAT segmentation on longitudinal MRI in adults with o...
Effects of grape juice intake on the cell migration properties in overweight women: Modulation mechanisms of cell migration in vitro by delphinidin-3-O-glucoside.
Food research international (Ottawa, Ont.)
Dec 19, 2023
Overweight and obesity are typical conditions of chronic low-intensity systemic inflammatory responses, and both have become more common in recent decades, which emphasizes the necessity for healthier diet intake. Fruits such as grapes are rich in an...
Reduced versus standard dose contrast volume for contrast-enhanced abdominal CT in overweight and obese patients using photon counting detector technology vs. second-generation dual-source energy integrating detector CT.
European journal of radiology
Oct 18, 2023
PURPOSE: To compare image quality of contrast-enhanced abdominal-CT using 1st-generation Dual Source Photon-Counting Detector CT (DS-PCD-CT) versus 2nd-generation Dual-Source Energy Integrating-Detector CT (DS-EID-CT) in patients with BMI ≥ 25, apply...
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