Obesity

Association between the oxidative balance score and depressive symptoms in adults with metabolic syndrome: a cross-sectional study from NHANES.

OBJECTIVE: This study investigated the association between the Oxidative Balance Score (OBS) and the odds of depressive symptoms in adults with metabolic syndrome (MetS) using National Health and Nutrition Examination Survey data (2007-2018), and employed machine learning to enhance predictive insights. METHODS: We analyzed 6,244 U.S. adults with MetS. Multivariable logistic regression assessed th...

Predicting rapid weight gain in six-month-old infants: an exploratory modeling study.

BACKGROUND: Rapid weight gain (RWG) in early life is a significant risk factor for childhood obesity. Its multifactorial etiology warrants exploratory statistical and machine-learning analysis to aid early prediction. METHODS: Data from a prospective infant study were used to compare four models for predicting RWG from birth to 6 months: two machine‑learning methods (SVM with a linear kernel and N...

Preoperative Risk Score for Mortality Within 3 Years of Elective Aortobifemoral Artery Bypass.

BACKGROUND: The purpose of this study was to create a risk score for mortality within 3 years of elective aortobifemoral artery bypass for aortoiliac ...

Wearable Sleep Measures May Improve Machine Learning Prediction of Home-Based Pulmonary Rehabilitation Engagement Among Patients With Chronic Obstructive Pulmonary Disease: A Proof-of-Concept Study.

OBJECTIVE: To evaluate whether incorporating baseline sleep measures from a wrist-worn activity monitor in machine learning (ML) models improved the p...

Gut microbial modulation of 3-hydroxyanthranilic acid and dopaminergic signalling influences attention in obesity.

BACKGROUND: Obesity-related alterations in the gut microbiota have been linked to cognitive decline, yet their relationship with attention remains poo...

MS360°: a conceptual digital-first, data-driven hybrid care framework for personalised multiple sclerosis management.

This perspective introduces MS360°, a conceptual hybrid care model for the management of multiple sclerosis (MS). It integrates traditional on-site as...

Modifiable risk factors associated with increased retinal age gap in an Australian population.

Retinal age gap (RAG)-the difference between retina-predicted age and chronological age-indicates biological ageing that has been linked to the risk o...

Body mass index and diet-related inflammation as predictors of sleep disorders: A cross-sectional study.

This study examines diet as a key risk factor for sleep disorders and integrates physiological indicators to develop a machine learning (ML)-based mod...

Motion capture dataset of 137 post-operative total hip replacement patients performing activities of daily living.

Three-dimensional motion capture is a powerful tool in clinical and engineering applications, but it can be time consuming, expensive, and difficult t...

Predicting VRE Infection After Liver Transplantation With a Time-Updated Colonization Score.

BACKGROUND: Vancomycin-resistant Enterococcus (VRE) infection is a life-threatening complication after liver transplantation (LT). This study aimed to...

Integrated prognostic evaluation of TyG and TyG-BMI in critically ill patients with comorbid atrial fibrillation and ischemic stroke using machine learning.

Machine learning prediction of weight gain after antiretroviral therapy initiation in people with HIV: Insights from a large french real-world cohort.

Excessive weight gain after initiation of antiretroviral therapy (ART) has become a recognized concern among people living with HIV. Individual weight...

Possible cross‑talk between sarcopenia and obstructive sleep apnea revealed by WGCNA analysis and machine learning.

BACKGROUND: Emerging evidence suggests a potential link between obstructive sleep apnea (OSA) and sarcopenia. OSA-induced hypoxia and sleep disturbanc...

Smartphone Detection of Fetal Movements Using Artificial Intelligence.

OBJECTIVE: To evaluate whether machine learning could be used with audio recordings from a smartphone to detect fetal movements that create disruption...

Artificial intelligence-derived electrocardiographic age gap as a predictor of mortality after coronary revascularization: prognostic value and short-term intra-patient variability.

AIMS: The artificial intelligence (AI)-derived electrocardiographic (ECG) age gap-the difference between AI-predicted ECG age and chronological age-is...

Early Prediction of Standing at Discharge in Moderate-to-Severe TBI: A Clinical Machine Learning Model Integrating Modifiable and Nonmodifiable Factors.

OBJECTIVE: To develop and internally validate a machine learning model to predict favorable standing ability at hospital discharge in patients with mo...

Multivariable AI-based analysis of immune-lifestyle patterns associated with recurrent pregnancy loss: an exploratory retrospective study.

Introduction Approximately 1-5% of pregnant women experience recurrent pregnancy loss (RPL). Early detection and evaluation of high-risk variables all...

Heterogeneous associations of a mobile health-based disease management program on uncontrolled hypertension: A target trial emulation study.

Long-term effectiveness of digital health interventions for hypertension remains unclear, particularly regarding individual variability in treatment r...

Assessment of socioeconomic and demographic risk factors for low birth weight using model-agnostic explainable ensembles.

BACKGROUND AND OBJECTIVE: Low birth weight (LBW) is a major global public health concern, strongly linked to neonatal morbidity and long-term health c...

Maternal Gut Microbiome as a Predictor of Insulin Therapy Requirement in Gestational Diabetes.

BACKGROUND: Gestational diabetes mellitus (GDM) often requires pharmacological intervention beyond lifestyle modification to achieve optimal glycemic ...