AIMC Topic: Obesity
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Comparing logistic regression and machine learning for obesity risk prediction: A systematic review and meta-analysis.
International journal of medical informatics
Jul 1, 2025
BACKGROUND: Logistic regression (LR) has traditionally been the standard method used for predicting binary health outcomes; however, machine learning (ML) methods are increasingly popular.
Assessment of Image Quality of Coronary Computed Tomography Angiography in Obese Patients by Comparing Deep Learning Image Reconstruction With Adaptive Statistical Iterative Reconstruction Veo.
Journal of computer assisted tomography
May 13, 2025
OBJECTIVE: The aim of the study was to evaluate the image quality of coronary computed tomography (CT) angiography (CCTA) in obese patients by using deep learning image reconstruction (DLIR) in comparison with adaptive statistical iterative reconstru...
Assessing online chat-based artificial intelligence models for weight loss recommendation appropriateness and bias in the presence of guideline incongruence.
International journal of obesity (2005)
May 1, 2025
BACKGROUND AND AIM: Managing obesity requires a comprehensive approach that involves therapeutic lifestyle changes, medications, or metabolic surgery. Many patients seek health information from online sources and artificial intelligence models like C...
Protocol for evaluating the cost-effectiveness of Mongolia's sugar-sweetened beverages tax using double machine learning.
PloS one
Jan 1, 2025
Elevated consumption of sugar-sweetened beverages (SSBs) has been associated with an increase in obesity, type 2 diabetes, and other non-communicable diseases (NCDs), a significant health and economic burden on Mongolia. To address this, the governme...
Effect of artificial intelligence driven therapeutic lifestyle changes (AI-TLC) intervention on health behavior and health among obesity pregnant women in China: a randomized controlled trial protocol.
Frontiers in public health
Jan 1, 2025
INTRODUCTION: Obesity has reached epidemic proportions globally, posing significant challenges to public health and economic stability. In China, the prevalence of obesity is increasing rapidly, particularly among pregnant women, who face unique risk...
Developing a machine learning algorithm to predict psychotropic drugs-induced weight gain and the effectiveness of anti-obesity drugs in patients with severe mental illness: Protocol for a prospective cohort study.
PloS one
Jan 1, 2025
Obesity is a global public health concern, often co-occurring in patients with severe mental illnesses. The impact of psychotropic drugs-induced weight gain is augmenting the disease burden and healthcare expenditure. However, predictors of psychotro...
Machine learning-based clustering identifies obesity subgroups with differential multi-omics profiles and metabolic patterns.
Obesity (Silver Spring, Md.)
Nov 1, 2024
OBJECTIVE: Individuals living with obesity are differentially susceptible to cardiometabolic diseases. We hypothesized that an integrative multi-omics approach might improve identification of subgroups of individuals with obesity who have distinct ca...
Study of obesity research using machine learning methods: A bibliometric and visualization analysis from 2004 to 2023.
Medicine
Sep 6, 2024
BACKGROUND: Obesity, a multifactorial and complex health condition, has emerged as a significant global public health concern. Integrating machine learning techniques into obesity research offers great promise as an interdisciplinary field, particula...
Deep learning-based BMI inference from structural brain MRI reflects brain alterations following lifestyle intervention.
Human brain mapping
Feb 15, 2024
Obesity is associated with negative effects on the brain. We exploit Artificial Intelligence (AI) tools to explore whether differences in clinical measurements following lifestyle interventions in overweight population could be reflected in brain mor...
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