Cardiovascular

Metabolic Syndrome

Latest AI and machine learning research in metabolic syndrome for healthcare professionals.

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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,...

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 me...

DiaBD: A diabetes dataset for enhanced risk analysis and research in Bangladesh.

Diabetes is a chronic condition affecting millions worldwide and severely impacts health and quality...

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...

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...

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 h...

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 im...

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

Pulmonary hypertension is a progressive condition characterized by increased pulmonary vascular pres...

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

Chronic thromboembolic pulmonary hypertension (CTEPH) is a potentially life-threatening condition, c...

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 f...

Blood pressure monitoring is key in aortic dissection.

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

Hypertension precision medicine: the promise and pitfalls of pharmacogenomics.

Pharmacogenomics (PGx) has the potential to revolutionize hypertension management by tailoring antih...

Comparison of seven machine learning models in hypertension classification using photoplethysmographic and anthropometric data.

This study presents an algorithm for classifying individuals into four hypertension categories (heal...

Predictive machine learning model for 30-day hospital readmissions in a tertiary healthcare setting.

MOTIVATION: Hospital readmissions represent a major challenge for healthcare systems due to their im...

Diagnostic and prognostic value of ECG-predicted hypertension-mediated left ventricular hypertrophy using machine learning.

OBJECTIVE: Four hypertension-mediated left ventricular hypertrophy (LVH) phenotypes have been report...

Integrating Artificial Intelligence and Precision Therapeutics for Advancing the Diagnosis and Treatment of Age-Related Macular Degeneration.

Age-related macular degeneration (AMD) is a multifactorial retinal disease influenced by complex mol...

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