AIMC Topic: Obesity
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Lipidomic profiling of human adiposomes identifies specific lipid shifts linked to obesity and cardiometabolic risk.
JCI insight
Jun 23, 2025
BACKGROUNDObesity, a growing health concern, often leads to metabolic disturbances, systemic inflammation, and vascular dysfunction. Emerging evidence suggests that adipose tissue-derived extracellular vesicles (adiposomes) may propagate obesity-rela...
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).
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...
Artificial intelligence in anti-obesity drug discovery: unlocking next-generation therapeutics.
Drug discovery today
Mar 17, 2025
Obesity, a multifactorial disease linked to severe health risks, requires innovative treatments beyond lifestyle changes and current medications. Existing anti-obesity drugs face limitations regarding efficacy, side effects, weight regain and high co...
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