AIMC Topic: Obesity
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Evaluating the relationship between environmental chemicals and obesity: Evidence from a machine learning perspective.
Ecotoxicology and environmental safety
Jun 6, 2025
Environmental chemicals are increasingly recognized as important contributors to obesity, yet the number of studies evaluating this relationship remains insufficient. This study aimed to investigate these associations using interpretable machine lear...
Methodological Review of Classification Trees for Risk Stratification: An Application Example in the Obesity Paradox.
Nutrients
May 31, 2025
BACKGROUND: Classification trees (CTs) are widely used machine learning algorithms with growing applications in clinical research, especially for risk stratification. Their ability to generate interpretable decision rules makes them attractive to hea...
Radiomic and proteomic signatures of body mass index on brain ageing and Alzheimer's-like patterns of brain atrophy.
EBioMedicine
May 27, 2025
BACKGROUND: The impact of high body mass index (BMI) states and associated proteomic factors on brain ageing and Alzheimer's disease (AD) remains unclear.
Leveraging Social Media Data to Understand the Impact of COVID-19 on Residents' Dietary Behaviors: Observational Study.
Journal of medical Internet research
May 23, 2025
BACKGROUND: The COVID-19 pandemic has inflicted global devastation, infecting over 750 million and causing 6 million deaths. In an effort to control the spread of the virus, governments around the world implemented a variety of measures, including st...
Meta-analysis of shotgun sequencing of gut microbiota in obese children with MASLD or MASH.
Gut microbes
May 21, 2025
Alterations in the gut microbiome affect the development and severity of metabolic dysfunction-associated steatotic liver disease (MASLD) or metabolic dysfunction-associated steatohepatitis (MASH). We analyzed microbiomes of obese children with and w...
Developing cardiac digital twin populations powered by machine learning provides electrophysiological insights in conduction and repolarization.
Nature cardiovascular research
May 16, 2025
Large-cohort imaging and diagnostic studies often assess cardiac function but overlook underlying biological mechanisms. Cardiac digital twins (CDTs) are personalized physics-constrained and physiology-constrained in silico representations, uncoverin...
Uncovering key factors in weight loss effectiveness through machine learning.
International journal of obesity (2005)
May 6, 2025
BACKGROUND/OBJECTIVES: One of the main challenges in weight loss is the dramatic interindividual variability in response to treatment. We aim to systematically identify factors relevant to weight loss effectiveness using machine learning (ML).
Promoting active health with AI technologies: Current status and prospects of high-altitude therapy, simulated hypoxia, and LLM-driven lifestyle rehabilitation approaches.
Bioscience trends
Apr 29, 2025
In the context of the rising global prevalence of obesity, traditional intervention measures have proven insufficient to meet the demands of personalized and sustainable health management, necessitating the exploration of innovative solutions through...
Development and validation of machine learning models for predicting low muscle mass in patients with obesity and diabetes.
Lipids in health and disease
Apr 29, 2025
BACKGROUND AND AIMS: Low muscle mass (LMM) is a critical complication in patients with obesity and diabetes, exacerbating metabolic and cardiovascular risks. Novel obesity indices, such as the body roundness index (BRI), conicity index, and relative ...
The Use of an Artificial Intelligence Platform OpenEvidence to Augment Clinical Decision-Making for Primary Care Physicians.
Journal of primary care & community health
Apr 16, 2025
BACKGROUND: Artificial intelligence (AI) platforms can potentially enhance clinical decision-making (CDM) in primary care settings. OpenEvidence (OE), an AI tool, draws from trusted sources to generate evidence-based medicine (EBM) recommendations to...
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