Hypertension

Machine Learning Quantification of Pulmonary Regurgitation Fraction from Echocardiography.

Assessment of pulmonary regurgitation (PR) guides treatment for patients with congenital heart disease. Quantitative assessment of PR fraction (PRF) by echocardiography is limited. Cardiac MRI (cMRI) is the reference-standard for PRF quantification. We created an algorithm to predict cMRI-quantified PRF from echocardiography using machine learning (ML). We retrospectively performed echocardiograph...

A comprehensive study on machine learning models combining with oversampling for bronchopulmonary dysplasia-associated pulmonary hypertension in very preterm infants.

BACKGROUND: Bronchopulmonary dysplasia-associated pulmonary hypertension (BPD-PH) remains a devastating clinical complication seriously affecting the therapeutic outcome of preterm infants. Hence, early prevention and timely diagnosis prior to pathological change is the key to reducing morbidity and improving prognosis. Our primary objective is to utilize machine learning techniques to build predi...

SleepBP-Net: A Time-Distributed Convolutional Network for Nocturnal Blood Pressure Estimation from Photoplethysmogram.

Nocturnal blood pressure (BP) monitoring offers valuable insights into various aspects of human wellbeing, particularly cardiovascular health. Despite...

CiGNN: A Causality-Informed and Graph Neural Network Based Framework for Cuffless Continuous Blood Pressure Estimation.

Causalityholds profound potentials to dissipate confusion and improve accuracy in cuffless continuous blood pressure (BP) estimation, an area often ne...

Application of machine learning for antibiotic resistance in water and wastewater: A systematic review.

Antibiotic resistance (AR) is considered one of the greatest global threats in the current century, which can only be overcome if all interconnected a...

Prediction and causal inference of hyperuricemia using gut microbiota.

Hyperuricemia (HUA) is a symptom of high blood uric acid (UA) levels, which causes disorders such as gout and renal urinary calculus. Prolonged HUA is...

Artificial Intelligence-Derived Risk Prediction: A Novel Risk Calculator Using Office and Ambulatory Blood Pressure.

BACKGROUND: Quantification of total cardiovascular risk is essential for individualizing hypertension treatment. This study aimed to develop and valid...

Integrating decision modeling and machine learning to inform treatment stratification.

There is increasing interest in moving away from "one size fits all (OSFA)" approaches toward stratifying treatment decisions. Understanding how expec...

Radiomics-based detection of acute myocardial infarction on noncontrast enhanced midventricular short-axis cine CMR images.

Cardiac magnetic resonance cine images are primarily used to evaluate functional consequences, whereas limited information is extracted from the nonco...

Text mining of hypertension researches in the west Asia region: a 12-year trend analysis.

More than half of the world population lives in Asia and hypertension (HTN) is the most prevalent risk factor found in Asia. There are numerous articl...

Nutritional management recommendation systems in polycystic ovary syndrome: a systematic review.

BACKGROUND: People with polycystic ovary syndrome suffer from many symptoms and are at risk of developing diseases such as hypertension and diabetes i...

DeepMesh: Mesh-Based Cardiac Motion Tracking Using Deep Learning.

3D motion estimation from cine cardiac magnetic resonance (CMR) images is important for the assessment of cardiac function and the diagnosis of cardio...

Diastolic function assessment with four-dimensional flow cardiovascular magnetic resonance using automatic deep learning E/A ratio analysis.

BACKGROUND: Diastolic left ventricular (LV) dysfunction is a powerful contributor to the symptoms and prognosis of patients with heart failure. In pat...

Prediction of cardiovascular and renal risk among patients with apparent treatment-resistant hypertension in the United States using machine learning methods.

Apparent treatment-resistant hypertension (aTRH), defined as blood pressure (BP) that remains uncontrolled despite unconfirmed concurrent treatment wi...

Biodegradation of ciprofloxacin using machine learning tools: Kinetics and modelling.

Recently, the rampant administration of antibiotics and their synthetic organic constitutes have exacerbated adverse effects on ecosystems, affecting ...

Predicting hypertension control using machine learning.

Hypertension is a widely prevalent disease and uncontrolled hypertension predisposes affected individuals to severe adverse effects. Though the import...

Reproducibility of artificial intelligence-enabled plaque measurements between systolic and diastolic phases from coronary computed tomography angiography.

OBJECTIVES: Current coronary CT angiography (CTA) guidelines suggest both end-systolic and mid-diastolic phases of the cardiac cycle can be used for C...

Prevalence and Risk Factors of Chronic Kidney Disease in the General Population in Abidjan, Côte d'Ivoire: A Cross-sectional Study.

Chronic kidney disease (CKD) is a major cause of morbidity and mortality worldwide, but few studies are available on CKD in Cote d'Ivoire. We aimed to...

A Survey on Blood Pressure Measurement Technologies: Addressing Potential Sources of Bias.

Regular blood pressure (BP) monitoring in clinical and ambulatory settings plays a crucial role in the prevention, diagnosis, treatment, and managemen...

Development of a machine learning-based model for predicting individual responses to antihypertensive treatments.

BACKGROUND AND AIMS: Personalized antihypertensive drug selection is essential for optimizing hypertension management. The study aimed to develop a ma...