Metabolic Syndrome

Automated Deep Learning-Based Detection of Early Atherosclerotic Plaques in Carotid Ultrasound Imaging

Carotid plaque presence is associated with cardiovascular risk, even among asymptomatic individuals. While deep learning has shown promise for carotid plaque phenotyping in patients with advanced atherosclerosis, its application in population-based settings of asymptomatic individuals remains unexplored. We developed a YOLOv8-based model for plaque detection using carotid ultrasound images from 19...

Breath-Based Monitoring of High Cholesterol State and Statin Therapy

Monitoring the effectiveness of statin therapy in patients with dyslipidemia is essential for ensuring optimal treatment outcomes. The current standard involves lipid profiling via blood tests to detect abnormalities in blood lipids. This study evaluated the feasibility of a non-invasive, breath-based approach to statin therapy monitoring using Noze’s electronic nose (eNose) platform. A total of 3...

Development of a Hypertension Risk Prediction Model using Nationally Representative Survey Data: A Machine Learning Approach and Web Application Deployment

Hypertension is a major modifiable risk factor for cardiovascular diseases. Early identification of high-risk individuals using predictive models can ...

Non-Traditional Lipid Ratios Predict Cardiovascular-Kidney-Metabolic Syndrome: Insights from Machine Learning Model Using NHANES Data

Cardiovascular-kidney-metabolic (CKM) syndrome is a newly defined multisystem disease continuum characterized by the coexistence of metabolic dysfunct...

Plasma Proteomics Linking Primary and Secondary diseases: Insights into Molecular Mediation from UK Biobank Data

Diabetes, hypertension, and dyslipidemia are major risk factors for cardiovascular (CVD), cerebral, and renal diseases (RD). However, the underlying m...

Machine Learning Prediction of Pharmacogenetic Test Uptake Among Opioid-Prescribed Patients Using Electronic Health Records: A Retrospective Cohort Study

Opioids are a widely prescribed class of medication for pain management. However, they have variable efficacy and adverse effects among patients, due ...

Comprehensive, Transparent, and Fair Machine Learning Models for Hypertension Risk Prediction: Benchmarking With Framingham, External Validation, Individual-Level Analysis, and Equitable Clinical Utility

Hypertension (HTN) is a leading, yet often underdiagnosed, cause of cardiovascular diseases worldwide. While clinical risk scores like the Framingham ...

Clustered Phenotypes of Hypertensive Heart Disease With Strain Measurements Reveals Distinct Characteristics, Clinical Course, and Prognosis

Hypertensive heart disease (HHD) encompasses diverse clinical profiles, comorbidities, and cardiac remodeling, but current classifications insufficien...

A Self-Explainable Dynamic Risk Monitoring Framework for Predicting Alzheimer’s Disease and Related Dementias

Alzheimer’s Disease and Related Dementias (ADRD) affect millions worldwide and can begin over a decade before symptoms appear. ADRD are generally irre...

Development of Machine Learning Models to Predict Hypoglycemia and Hyperglycemia on Days of Hemodialysis in Patients with Diabetes based on Continuous Glucose Monitoring

Patients with diabetes undergoing hemodialysis (HD) are at risk of asymptomatic hypo- and hypergly-cemia within 24 hours of dialysis. Continuous gluco...

Statistical Applications in Pediatric Endocrinology: A Simulation on Metformin’s Effect on HbA1c in High-Risk Adolescents

Metformin has been increasingly used off-label in adolescents with type 1 diabetes (T1D) or prediabetic conditions to improve glycemic control. Despit...

Combination AI-Machine Learning to Diagnose Pulmonary Hypertension: A Real-World Evidence Cohort Study

Pulmonary hypertension (PH) is a highly morbid disease, but underdiagnosis is common outside of expert referral centers. Consequentially, there may be...

Machine Learning Risk Prediction for Prolonged Hospitalization in Frail Older Adults with Multimorbidity

Frailty and multimorbidity are common in older adults and contribute substantially to prolonged hospitalizations, readmissions, and mortality. Yet, ex...

A Metabolic-Inflammatory Phenotype of Pelvic Floor Dysfunction: A Machine Learning-Based Discovery in a Nationally Representative U.S. Cohort

Pelvic floor dysfunction (PFD) is a highly prevalent and heterogeneous condition among women. The traditional view of PFD as a single clinical entity ...

Metformin use is associated with lower mortality from bacterial sepsis and improved immunocompetence in Thai diabetes patients with acute melioidosis

Diabetes mellitus (DM) is a major risk factor for acquiring infections. Metformin, the first-line treatment for type 2 DM, is associated with benefici...

A photoplethysmography-based aging clock reveals genetic determinants of arterial aging

Arterial aging, marked by progressive vascular stiffening, is a contributor to cardiovascular disease. Photoplethysmography (PPG) waveforms offer an e...

Circulating Metabolites are Linked to Dementia and Brain Imaging Phenotypes, and Mediate Modifiable Risk Pathways

Dementia poses an escalating global health burden, yet its underlying mechanisms remain incompletely understood. In this large-scale, targeted metabol...

RAGCBPNet: An Efficient Feature Fusion Framework for Wearable Cuffless Blood Pressure Monitoring and Long-term Validation in Real-world Settings

Wearable and cuffless blood pressure (BP) monitoring hold great promise for preventive hypertension management, yet few studies have been validated un...

Medication-Stratified Analysis of LDL-C Equation Miscalibration in Diabetes: Evidence from the All of Us Research Program and a Medication-Agnostic Machine-Learning Correction

Standard LDL-C equations were derived in cohorts largely untreated with modern combination diabetes therapies. With medication-treated patients compri...

Comparing different types of machine learning models in diagnosing diabetes mellitus utilizing electrocardiography and clinical data

Diabetes Mellitus (DM) represents one of the most significant global public health challenges of the 21st century. This dramatic increase in the preva...