Obesity

Identifying risk factors for marijuana use among male high school students using machine learning: Implications for public health.

OBJECTIVES: To identify risk and protective factors associated with lifetime marijuana use among male high school students through an interpretable machine learning model, providing evidence to support early and targeted public health interventions. STUDY DESIGN: Cross-sectional analysis of 2023 Youth Risk Behavior Surveillance System (YRBS) data for boys in grades 9-12 across the United States. M...

Machine learning for precision obstetrics: A comprehensive review of risk prediction models for hypertensive disorders and pregnancy-related syndromes.

Gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy (HDP), preterm birth, and intrauterine growth restriction represent major contributors to maternal and neonatal morbidity worldwide. Traditional screening methods relying on single biomarkers or linear models often demonstrate limited predictive accuracy. This review examines the transformative role of machine learning (ML) i...

Single-photon emission computed tomography/computed tomography-based radiomics of bone metastases for predicting epidermal growth factor receptor mutation status and targeted therapy efficacy in non-small-cell lung cancer.

BACKGROUND: This study aimed to develop a single-photon emission computed tomography/computed tomography (SPECT/CT)-based radiomics model using bone m...

The Evolution of Bariatric and Metabolic Surgery in the Artificial Intelligence Era: A Comprehensive Systematic Review of Current Applications and Clinical Implications.

BACKGROUND: Artificial intelligence (AI) uses in the field of bariatric and metabolic surgery (BMS) have evolved over the past few years. However, pub...

Machine Learning-Based Risk Prediction of In-Hospital Mortality in Patients With Non-ST-Elevation Acute Coronary Syndrome at Various Stages of the Diagnostic Process: Observational Study.

BACKGROUND: Despite advances in understanding and treating non-ST-elevation acute coronary syndrome (NSTE-ACS), patients continue to experience high r...

Multidimensional Analysis of Early Adiposity Rebound Determinants in Children: Two Key "1000 Days".

OBJECTIVE: Adiposity rebound (AR), the second rise in BMI during growth, increases the risk of obesity and metabolic diseases when it occurs early. We...

Correlates of physical activity behaviour in a population sample with increased cardiovascular risk and established cardiovascular disease: Cross-sectional analysis of data from the Paracelsus 10,000 prospective cohort study in Salzburg, Austria.

Regular physical activity (PA) remains challenging for many people with high cardiovascular risk and established cardiovascular disease (CVD). We aime...

Percutaneous thermal ablation for renal cell carcinoma: a comprehensive review of current evidence and future directions.

Thermal ablation (TA), including microwave ablation, radiofrequency ablation, and cryoablation, is increasingly used as a surgical alternative for T1a...

Artificial intelligence-enhanced management system for secondary prevention of coronary heart disease: a randomized clinical trial.

BACKGROUND: Secondary prevention of coronary heart disease (CHD) remains suboptimal due to fragmented care and therapeutic inertia. While digital heal...

Prognostication in End-Stage Kidney Disease: Tools, Evidence, and Clinical Applications.

Prognostication in end-stage kidney disease is fundamental to person-centered care and shared decision-making. This review summarizes the current evid...

Cohort Profile Update: the Rotterdam Periconceptional Cohort-biomarkers, lifestyle intervention, and artificial intelligence.

Clustering of rheumatoid arthritis patients: an unsupervised machine learning approach for characterizing the TNFi response.

This study aimed to identifydistinct profiles of response to Tumor Necrosis Factor inhibitors (TNFi) in rheumatoid arthritis (RA) patients using unsup...

The Invisible Workforce: An Algorithmic Audit of Nursing, Primary Care, and Holistic Gaps in AI-Generated Survivorship Plans.

OBJECTIVES: Advanced ovarian cancer survivorship requires multidisciplinary coordination. As patients use large language models (LLMs) as clinical nav...

Systematic Review of the Relationship Between the Presence and Quality of Sidewalks and Children's Physical Health.

BACKGROUND: This systematic review synthesized existing research about associations between sidewalk availability and quality and children's physical ...

The impact of silicone oil on the formation of free fatty acids particles.

Silicone oil is a ubiquitous presence throughout the life cycle of biopharmaceutical products, originating from manufacturing processes and primary pa...

A Combined Deep Learning Approach to Screen Patients for Neuromuscular Pathology.

Neuromuscular diseases (NMD), comprising over 600 different conditions, severely impact nerve and/or muscle function and lead to significant morbidity...

Machine Learning-Derived Sarcopenia Signature Identifies High-Risk Molecular State in T2D Skeletal Muscle.

Sarcopenia is common in type 2 diabetes (T2D), but whether sarcopenia-associated transcriptomic features can be detected in diabetic skeletal muscle r...

NMR metabolomics and glycomics for cancer detection in patients with non-specific symptoms: a prospective observational cohort study.

BACKGROUND: Early cancer diagnosis in patients with non-specific symptoms is limited by the lack of discriminatory tests. Within the Oxfordshire Suspe...

"Early Stratification of Risk for Poor Neurological Outcome After Cardiac Arrest Is Improved with Processed EEG Data".

AIM: To evaluate the impact of adding early processed quantitative EEG biomarkers to health record data for early neurological risk stratification aft...

Histological aging signatures for monitoring tissue-specific aging and disease.

Aging is the primary risk factor for chronic disease and is characterized by profound structural and architectural remodeling of human tissues. Here, ...