Metabolic Syndrome

Predicting pulmonary hemodynamics in pediatric pulmonary arterial hypertension using cardiac magnetic resonance imaging and machine learning: an exploratory pilot study.

PURPOSE: Pulmonary arterial hypertension (PAH) significantly affects the pulmonary vasculature, requiring accurate estimation of mean pulmonary arterial pressure (mPAP) and pulmonary vascular resistance index (PVRi). Although cardiac catheterization is the gold standard for these measurements, it poses risks, especially in children. This pilot study explored how machine learning (ML) can predict p...

Searching for peripheral proteomic markers of primary aldosteronism.

PURPOSE: Primary aldosteronism (PA) is prevalent among hypertensive patients, and associated with worsened cardiovascular outcomes compared to essential hypertension (HT). Screening and diagnostics for PA are currently complicated and invasive, why new methods are needed. Unilateral PA (uPA) is best treated surgically, and bilateral PA (bPA) - medically. No validated proteomic diagnostic test has ...

Association between metal mixture in urine and abnormal blood pressure and mediated effect of oxidative stress based on BKMR and Machine learning method.

BACKGROUND: Exposure to heavy metals represents a significant risk factor for hypertension and blood pressure disorders. Notably, current evidence ind...

Gene as a Molecular Target Potentially Shared by Idiopathic Pulmonary Fibrosis and Pulmonary Hypertension: Drug Repurposing Prospect with Aminoglutethimide.

Idiopathic pulmonary fibrosis (IPF) and pulmonary hypertension (PH) are two chronic conditions that can coexist occasionally, resulting in high morbid...

Identification of lipid metabolism-associated biomarkers in lupus nephritis by SVM model and therapeutic potential of Alisol B 23-acetate.

Systemic lupus erythematosus (SLE), a multifaceted autoimmune disorder, has lupus nephritis (LN) as one of its grave complications and is strongly ass...

Association of urinary metal elements with sarcopenia and glucose metabolism abnormalities: Insights from NHANES data using machine learning approaches.

BACKGROUND: Sarcopenia, a condition marked by the decline of skeletal muscle mass and function, is prevalent in the elderly and closely linked to abno...

A hybrid GAN-based deep learning framework for thermogram-based breast cancer detection.

Breast cancer remains one of the most prevalent and life-threatening diseases among women worldwide, necessitating early and accurate detection method...

Out-of-distribution reject option method for dataset shift problem in early disease onset prediction.

Machine learning is increasingly used to predict lifestyle-related disease onset using health and medical data. However, its predictive accuracy for u...

Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis.

Diabetes Mellitus is a chronic metabolic disorder affecting a substantial global population leading to complications such as retinopathy, nephropathy,...

The Application of Machine Learning in Warfarin Dose Precision for Diabetic Patients Treated with Statins: A Comparative Study.

PURPOSE: To evaluate the impact of statin therapy on warfarin dose requirements in diabetic patients and to assess the performance of various machine ...

Assessing the stress hyperglycemia ratio in hyperlipidemia patients to predict all-cause mortality: A retrospective cohort study.

BACKGROUND: The Stress Hyperglycemia Ratio (SHR) reflects stress-related hyperglycemia and is linked to poor outcomes in various diseases. This study ...

Revolutionizing diabetes care: the role of artificial intelligence in prevention, diagnosis, and patient care.

UNLABELLED: Millions of people worldwide have diabetes, a disease that is becoming more common and has substantial socioeconomic costs. Artificial int...

Evaluating the impact of metabolic indicators and scores on cardiovascular events using machine learning.

Cardiovascular diseases such as coronary artery disease, myocardial infarction, and heart failure impact millions of people annually globally and are ...

The use of imaging in the diagnosis and treatment of thromboembolic pulmonary hypertension.

Chronic thromboembolic pulmonary hypertension (CTEPH) is a potentially life-threatening condition, classified as group 4 pulmonary hypertension (PH), ...

Determinants of artificial intelligence electrocardiogram-derived age and its association with cardiovascular events and mortality: a systematic review and meta-analysis.

Artificial intelligence (AI)-ECG-derived age (AI-ECG age) and Heart Delta Age (HDA)-the difference between AI-ECG and chronological age-are emerging t...

Gut microbiota, metabolites, and pulmonary hypertension: Mutual regulation and potential therapies.

Pulmonary hypertension is a progressive condition characterized by increased pulmonary vascular pressure and resistance, ultimately leading to right h...

Association between the stress hyperglycemia ratio and all-cause mortality in patients with hemorrhagic stroke: a retrospective analysis based on MIMIC-IV database.

BACKGROUND: Research on the associations between the stress hyperglycemia ratio (SHR) and adverse outcomes in patients with hemorrhagic stroke is limi...

Blood pressure monitoring is key in aortic dissection.

Blood pressure (BP) control is essential for both the prevention and long-term management of aortic dissection. While office BP monitoring remains the...

Improving ACS prediction in T2DM patients by addressing false records in electronic medical records using propensity score.

Our study aims to improve the prediction performance of machine learning (ML) models by addressing false records (i.e., false positive, false negative...

Hypertension precision medicine: the promise and pitfalls of pharmacogenomics.

Pharmacogenomics (PGx) has the potential to revolutionize hypertension management by tailoring antihypertensive therapy based on genetic profiles. Des...