Obesity

Explainable artificial intelligence for personalized prognosis in pancreatic cancer: A nationwide study from Taiwan.

Pancreatic cancer is highly aggressive with poor outcomes; current artificial intelligence (AI) prognostic models often lack interpretability and underutilize large-scale data. This study develops an explainable AI prognostic model for pancreatic cancer survival using Taiwan's national registry data, aiming to identify key prognostic factors, their interactions, non-linear relationships, and patie...

Associations between 12 insulin resistance surrogates with metabolic dysfunction-associated steatotic liver disease risk and all-cause mortality: data from the NHANES III (1988-1994).

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) has been shown to be intimately linked to the presence of insulin resistance. This study aimed to comprehensively evaluate 12 insulin resistance surrogates in relation to MASLD risk and all-cause mortality, utilizing nationwide data from the National Health and Nutrition Examination Survey (NHANES) III (1988-1994). METHOD...

Thymic health consequences in adults.

The thymus is essential for establishing T cell diversity early in life, but undergoes profound involution with age and has therefore traditionally be...

Deep Learning Echocardiographic Trajectories of Heart Failure With Preserved Ejection Fraction: A Retrospective Cohort Study.

BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) is a dynamic chronic disease. Specific disease trajectories remain unclear. OBJECTI...

Discovering anti-obesity blue food compounds via combined deep learning and in silico approaches.

The Burden, Outcomes, and Management of Patients with Aldosterone Dysregulation: A Targeted Literature Review.

INTRODUCTION: Aldosterone dysregulation (excess aldosterone production at the source within the adrenal glands) in the absence of primary aldosteronis...

Risk-prediction models for postpartum depression: Assessment of risk of bias using PROBAST+AI.

OBJECTIVE: The postpartum depression (PPD) risk prediction model is an effective risk stratification tool and is expected to play a significant role i...

Explainable artificial intelligence for early Alzheimer's diagnosis using enhanced grey relational features and multimodal data.

Alzheimer's disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of...

Limited validity of an AI-powered app for dietary assessment in females with obesity.

Artificial intelligence (AI) is transforming dietary assessment, yet few tools have been clinically validated against physiological reference methods....

Data-Driven Phenotypic Clusters of Gestational Diabetes Mellitus and Associations With Risk of Perinatal Complications and Postpartum Diabetes.

OBJECTIVE: Management of gestational diabetes mellitus (GDM) largely follows a uniform approach, despite growing recognition of GDM heterogeneity. We ...

Deep survival modelling to predict future cognitive impairment in unimpaired adults.

BACKGROUND: Predicting Alzheimer's disease (AD)-related cognitive impairment (CI) among cognitively normal (CN) adults enables meaningful disease modi...

Adiposome Lipidomic Shifts Following Bariatric Surgery in Association With Weight Loss and Cardiometabolic Benefit.

CONTEXT: Adiposomes carry bioactive lipids that shape systemic metabolism and vascular function. OBJECTIVE: Building on our previous findings that obe...

Joint effects of physical activity and diet quality on depressive symptoms and all-cause mortality in adults with diabetes: NHANES 2007-2018.

Depressive symptoms are common among adults with diabetes and are associated with adverse clinical outcomes, including mortality. Evidence from genera...

Longitudinal prediction of BMI using explainable AI: integrating polygenic scores, maternal, early-life and familial factors.

BACKGROUND/OBJECTIVES: This study aimed to predict body mass index (BMI) trajectories from childhood to early adulthood using explainable artificial i...

Insulin resistance prediction from wearables and routine blood biomarkers.

Insulin resistance (IR), a primary precursor to type 2 diabetes, is characterized by impaired insulin action in tissues1. However, diagnostic methods ...

Integrating phenotypic information of obstructive sleep apnea and deep representation of sleep-event sequences for cardiovascular risk prediction.

BACKGROUND: Advances in wearable and machine learning technologies have opened new possibilities for predicting cardiovascular (CV) risk. Moreover, th...

Patient Perceptions of Artificial Intelligence in Diabetes Self-Management: Cross-Sectional Survey Study.

BACKGROUND: Artificial intelligence (AI) is increasingly applied in chronic disease management, including diabetes, where it has the potential to supp...

Machine Learning Prediction of Progression to Dialysis in Patients With Polycystic Kidney Disease: Population-Based Retrospective Cohort Study.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD), characterized by progressive cyst growth and renal decline, is the leading genetic c...

Development of death-risk score based on epidemiology of six mental disorders and application to mortality reduction via modifiable health behaviors.

OBJECTIVE: Prediction models for mortality rarely incorporate diverse psychiatric conditions, alongside clinical, behavioral, and demographic risk fac...

Unsupervised identification of muscle phenotypes in adults with obesity: a data-driven framework for the identification of sarcopenia in absence of a gold standard.

BACKGROUND: Sarcopenia is characterized by progressive loss of skeletal muscle mass and strength and is associated with increased disability and morta...