Obesity

Phenotyping population-level chronic condition prevalence: The importance of forcing factors from the ecological framework.

OBJECTIVE: The primary health challenges currently facing the United States (U.S.) and many other countries around the world are largely due to patients with chronic conditions, which act either independently or synergistically. The current study assesses the ability of the Ecological Framework of Population Health to predict U.S. county-level prevalences of eight common chronic conditions. STUDY ...

Metabolomic and lifestyle profiles refine BMI-metabolic phenotypes in older adults.

Conventional BMI-based classifications, even when combined with traditional cardiometabolic risk factors, limit precision in aging-related risk assessment. Here, we perform metabolomic analysis in 13,202 older adults from the natural aging cohort (NCT04517513). Leveraging a panel of 39 core metabolites, we develop accurate and interpretable machine learning models to identify metabolic dysfunction...

TCEP Induces Liver Injury Through Suppression of the PI3K/AKT Axis: Integrated Evidence from Epidemiology, Network Toxicology, and In Vivo Validation.

Tris(2-chloroethyl) phosphate (TCEP) is a widely used chlorinated organophosphate flame retardant, but its role in liver injury remains unclear. In th...

Psoriatic Disease Across Dimensions: Global Epidemiology, Comorbidity, and Artificial Intelligence in Treatment Prediction.

The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2025 annual meeting featured a new "Soapbox: Rapid fire presentati...

Cross-ancestry pleiotropic analysis of imaging-derived phenotypes enhances risk stratification of depression.

Depression arises from dynamic interactions among genetic predisposition, brain alterations, and environmental stressors. Despite genome-wide associat...

Decision tree-based prediction of 5-year weight trajectories after bariatric surgery in adolescents and young adults: a retrospective cohort study from France and Sweden.

BACKGROUND: Metabolic-bariatric surgery is an efficient therapy in selected adolescents with severe obesity. However, predicting the postoperative wei...

Predicting the Complex, Multilevel Ecology of US County-Level Diabetes Prevalence: A Cross-Sectional, Artificial Intelligence Analysis.

BACKGROUND: Diabetes and its risk factors are embedded in a complex multilevel ecology. Upstream factors (i.e., 'forcing factors' that refer to fundam...

Using Natural Language Processing of Clinical Notes to Supplement Structured Electronic Health Record Data for Phenotyping Smoking and Obesity in a Healthcare System.

PURPOSE: Studies based on electronic health records (EHR) often rely on structured data, which may incompletely capture important clinical phenotypes ...

Time-dependent predictive contribution of the triglyceride-glucose index for incident cardiovascular disease in a 9-year Chinese cohort.

This study aims to investigate the association between triglyceride-glucose (TyG) index and risk of CVD using explainable survival analysis method bas...

Comparative machine learning approaches to prognosticate clinical outcomes in oral and maxillofacial space infections: a retrospective analysis.

BACKGROUND: The objective of this study was to evaluate the performance of multiple machine learning algorithms to provide evidence supporting early i...

Prognostic models for diabetic kidney disease outcomes: A systematic review.

OBJECTIVE: This systematic review aimed to systematically evaluate the methodological quality and predictive performance of existing prognostic models...

Epigenetic-Genetic Crosstalk at the Cancer-Diabetes Interface: Convergent Molecular Pathways, Multi-Omics Biomarkers, and Dual Therapeutic Targets.

The complex interdependence between cancer and diabetes has become a major subject of research in molecular medicine since multiple data points indica...

Machine learning-based cross-sectional exploration of depression-chronic pain associations in chronic respiratory disease patients.

BACKGROUND: Chronic respiratory diseases (CRD) are a leading global cause of death, with high comorbidity rates of depression and chronic pain forming...

Deep learning analysis of ECGs detects Cardiovascular-Kidney-Metabolic syndrome burden in people with diabetes: a report from the Silesia Diabetes-Heart Project.

BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome refers to the co-occurrence of obesity, diabetes, chronic kidney disease (CKD), and cardiov...

Classification of functional movement screening scores and reported fall-incident history from deep squat videos among logistics service workers using deep learning.

Logistics service workers (LSWs) face a high risk of fall-related injuries owing to the physically demanding nature of their work. This study aimed to...

Glycemic variability does not provide incremental prognostic value for in-hospital death in community-acquired pneumonia patients: conventional clinical variables dominate.

OBJECTIVES: This study aimed to systematically evaluate whether glycemic variability (GV) could provide independent incremental prognostic value for i...

Temporal deep learning for 28-day mortality prediction in critically ill ovarian cancer patients: a multicenter development and validation study using hourly vital signs.

BACKGROUND: Ovarian cancer patients requiring intensive care unit (ICU) admission face particularly grave prognosis, yet current prognostic models rel...

A machine learning-based analysis of chronotype and sleep quality as predictors of mental distress in university students.

This cross-sectional study aimed to investigate the combined effects of chronotype, Mediterranean diet adherence, and sleep quality on mental distress...

Decoding the Complexity of Tricuspid Regurgitation Prognostic Drivers Using Explainable Artificial Intelligence.

AIMS: Prognosis in tricuspid regurgitation (TR) is shaped by complex clinical and hemodynamic interactions, complicating risk stratification. We aimed...

Machine learning classification and regional differentiation of neuropathologically-confirmed Alzheimer's disease and comorbid Lewy body disease.

BACKGROUND: Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) co-occur frequently, and growing evidence, including neuropathology, supports...