AIMC Topic: Obesity
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The Bioprotective Effects of Marigold Tea Polyphenols on Obesity and Oxidative Stress Biomarkers in High-Fat-Sugar Diet-Fed Rats.
Cardiovascular therapeutics
Oct 4, 2024
The research is aimed at exploring the potential of marigold petal tea (MPT), rich in polyphenol contents, against oxidative stress and obesity in a rat model following a high-fat-sugar diet (HFSD). The MPT was prepared through the customary method...
Estimating the prevalence of select non-communicable diseases in Saudi Arabia using a population-based sample: econometric analysis with natural language processing.
Annals of Saudi medicine
Oct 3, 2024
BACKGROUND: Non-communicable diseases (NCDs) are a major public health challenge globally, including in Saudi Arabia. However, measuring the true extent of NCD prevalence has been hampered by a paucity of nationally representative epidemiological stu...
Visualization obesity risk prediction system based on machine learning.
Scientific reports
Sep 28, 2024
Obesity is closely associated with various chronic diseases.Therefore, accurate, reliable and cost-effective methods for preventing its occurrence and progression are required. In this study, we developed a visualized obesity risk prediction system b...
Applying machine learning approaches for predicting obesity risk using US health administrative claims database.
BMJ open diabetes research & care
Sep 26, 2024
INTRODUCTION: Body mass index (BMI) is inadequately recorded in US administrative claims databases. We aimed to validate the sensitivity and positive predictive value (PPV) of BMI-related diagnosis codes using an electronic medical records (EMR) clai...
Maternal dietary practices during pregnancy and obesity of neonates: a machine learning approach towards hierarchical and nested relationships in a Tibet Plateau cohort study.
The British journal of nutrition
Sep 26, 2024
Studies on obesity and risk factors from a life-course perspective among residents in the Tibet Plateau with recent economic growth and increasing obesity are important and urgently needed. The birth cohort in this area provides a unique opportunity ...
Development and validation of cardiometabolic risk predictive models based on LDL oxidation and candidate geromarkers from the MARK-AGE data.
Mechanisms of ageing and development
Sep 14, 2024
The predictive value of the susceptibility to oxidation of LDL particles (LDLox) in cardiometabolic risk assessment is incompletely understood. The main objective of the current study was to assess its relationship with other relevant biomarkers and ...
Association of N-terminal pro-B natriuretic peptide with all-cause mortality and cardiovascular mortality in obese and non-obese populations and the development of a machine learning prediction model: National Health and Nutrition Examination Survey (NHANES) 1999-2004.
Diabetes, obesity & metabolism
Sep 6, 2024
AIMS: To explore the potential of N-terminal pro-B natriuretic peptide (NTproBNP) in identifying adverse outcomes, particularly cardiovascular adverse outcomes, in a population with obesity, and to establish a risk prediction model.
Deep Learning-Based Obesity Identification System for Young Adults Using Smartphone Inertial Measurements.
International journal of environmental research and public health
Sep 4, 2024
Obesity recognition in adolescents is a growing concern. This study presents a deep learning-based obesity identification framework that integrates smartphone inertial measurements with deep learning models to address this issue. Utilizing data from ...
Obesity prediction: Novel machine learning insights into waist circumference accuracy.
Diabetes & metabolic syndrome
Aug 29, 2024
AIMS: This study aims to enhance the precision of obesity risk assessments by improving the accuracy of waist circumference predictions using machine learning techniques.
Metabolic dysfunctions predict the development of Alzheimer's disease: Statistical and machine learning analysis of EMR data.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Aug 14, 2024
INTRODUCTION: The incidence of Alzheimer's disease (AD) and obesity rise concomitantly. This study examined whether factors affecting metabolism, race/ethnicity, and sex are associated with AD development.
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