Obesity

Genome-wide association analysis reveals specialization to hosts and niches in multiple species of the Lactobacillaceae.

The Lactobacillaceae inhabit diverse environments, but the extent of their habitat adaptation remains unclear and the colonization factors unknown. First, we applied multiple machine learning models to determine if we can distinguish strains of the same species isolated from two different habitats based on their gene content. Surprisingly, we show that no species is differentially adapted to the o...

Correction to: Machine and Deep Learning Models for Preoperative Prediction of Suboptimal Clinical Response One Year after Metabolic Bariatric Surgery: Findings from the Tehran Obesity Treatment Study.

Skeletal muscle reprogramming of metabolic, ribosomal and developmental pathways contributes to Roux-en-Y gastric bypass-induced adaptation in women.

BACKGROUND: Understanding how skeletal muscle responds to weight loss is crucial for developing targeted strategies to manage obesity and promote sust...

Three-class obstructive sleep apnea severity assessment: a parallel AHI and ODI explainable artificial intelligence framework using craniofacial-enriched clinical data.

BACKGROUND: Machine learning models for Obstructive Sleep Apnea (OSA) diagnosis have largely inherited some structural limitations: reliance on generi...

Cardiovascular risks of plastic-associated chemicals: Integrating mixture modeling and SHAP-explained machine learning to unravel linear and non-linear associations.

INTRODUCTION: Plastic-associated chemicals (PACs) are widely detected environmental contaminants, yet their cardiovascular relevance in the context of...

Integrating Multimodal Data and Genomics for a Comprehensive Assessment of Cardiovascular Aging and Its Impact.

BACKGROUND: Age-related structural and functional remodeling of the heart and vessels increases cardiovascular disease (CVD) risk, yet comprehensive a...

Metabolites stratify future major depressive disorder risk in obese population: a longitudinal machine learning analysis.

BACKGROUND: Obesity is a well-established risk factor for major depressive disorder (MDD), yet the risk is not uniform, highlighting the need for prec...

Mortality risk estimation for autistic older adults: comparing novel machine-learning derived weights versus standard weights for the Charlson Comorbidity Index.

Aim: We aimed to compare Quan and colleagues (2011) established weights for the Charlson Comorbidity Index (CCI) conditions to autism-specific weights...

Predicting future brain atrophy based on longitudinal MRI.

BackgroundNeuron loss is a hallmark of neurodegenerative diseases and leads to brain atrophy detectable with magnetic resonance imaging (MRI). Accurat...

Classification of malignant/benign groups in lung cancer by machine learning and investigation of feature significance of parameters.

OBJECTIVES: This study aimed to apply machine learning (ML) models to enhance lung cancer (LC) classification, distinguishing malignant from benign tu...

Agreement between markerless and marker-based motion capture for knee kinematics and kinetics during functional activities in knee osteoarthritis.

OBJECTIVE: To assess the agreement between markerless and marker-based motion capture for measuring knee kinematics and kinetics during functional act...

NeuroOmics-Net: An interpretable multimodal deep learning framework for Alzheimer's disease diagnosis and progression prediction using neuroimaging, EEG, and genomic data.

Accurate diagnosis and progression prediction of Alzheimer's disease (AD) remain challenging due to the heterogeneous nature of the disease, which inv...

Preoperative Optimization for Ventral Hernia Repair: Augmented Evidence Review.

BACKGROUND: Preoperative optimization is widely recommended for patients undergoing ventral hernia repair. However, the clinical impact of individual ...

BMI-based prediction models for short-term and long-term mortality following coronary artery bypass grafting using the MIMIC-IV database: a retrospective cohort study.

OBJECTIVE: This study aims to evaluate the relationship between obesity (measured by Body Mass Index (BMI)) and postoperative mortality in patients un...

Predicting which colorectal cancer patients are most likely to improve their functional capacity with pre-surgery prehabilitation: a retrospective study based on the 6-min walk distance.

PURPOSE: Prehabilitation prior to colorectal cancer (CRC) surgery aims to improve functional capacity and postoperative outcomes, although results rem...

Phenotypic Clustering of Idiopathic Pulmonary Arterial Hypertension: Insights Into Pulmonary Vascular and Cardiometabolic Co-Morbidity Trajectories.

Idiopathic pulmonary arterial hypertension (IPAH) exhibits significant clinical heterogeneity, necessitating a precision medicine approach. This study...

Risk Factors for Coronary Heart Disease and Stroke Among Older Adults With Metabolic Dysfunction-Associated Steatotic Liver Disease: A Nationwide Cohort Study.

BACKGROUND: Older adults with metabolic dysfunction-associated steatotic liver disease have elevated cardiovascular disease (CVD) risk, yet convention...

Systems-level genomic analyses reveal shared mechanisms underlying endometriosis and sleep disorders.

We examined clinical, genetic, and molecular links between sleep disorders and endometriosis. Women aged 20-54 years in NHANES 2005-2006 were analyzed...

Machine learning-based identification of cardiovascular risk modifiers in patients with very high LDL cholesterol: A cross-sectional study.

Individuals with LDL cholesterol (LDL-C) ≥ 190 mg/dL face a markedly increased risk of major adverse cardiovascular events (MACE). Traditional risk ca...

Accelerated 7T 3D DESS MR Neurography of the Cervical Spine Using CS-CAIPIRINHA and Deep Learning Reconstruction.

OBJECTIVE: To evaluate the potential of combined coherent and incoherent undersampling with deep learning (DL) reconstruction for highly accelerated h...