Hypertension

End-systole and end-diastole detection in short axis cine MRI using a fully convolutional neural network with dilated convolutions.

The correct assessment and characterization of heart anatomy and functionality is usually done throu...

Empirical analyses and simulations showed that different machine and statistical learning methods had differing performance for predicting blood pressure.

Machine learning is increasingly being used to predict clinical outcomes. Most comparisons of differ...

Integrated Learning Model-Based Assessment of Enteral Nutrition Support in Neurosurgical Intensive Care Patients.

To observe the clinical efficacy of early enteral nutrition application in critically ill neurosurgi...

Arterial Hypertension and the Hidden Disease of the Eye: Diagnostic Tools and Therapeutic Strategies.

Hypertension is a major cardiovascular risk factor that is responsible for a heavy burden of morbidi...

Follow-Up of Robotic Mitral Valve Repair: A Single Tertiary Institution Experience in China.

Surgical treatment of mitral valve diseases has become minimally invasive. This study analyzed the f...

Evaluating machine learning classifiers for glaucoma referral decision support in primary care settings.

Several artificial intelligence algorithms have been proposed to help diagnose glaucoma by analyzing...

Prediction of serious outcomes based on continuous vital sign monitoring of high-risk patients.

Continuous monitoring of high-risk patients and early prediction of severe outcomes is crucial to pr...

A Detailed Systematic Review on Retinal Image Segmentation Methods.

The separation of blood vessels in the retina is a major aspect in detecting ailment and is carried ...

A new deep learning framework based on blood pressure range constraint for continuous cuffless BP estimation.

Blood pressure (BP) is known as an indicator of human health status, and regular measurement is help...

An Artificial Intelligence-Enhanced Blood Pressure Monitor Wristband Based on Piezoelectric Nanogenerator.

Hypertensive patients account for about 16% to 37% of the global population, and about 9.4 million p...

Training and clinical testing of artificial intelligence derived right atrial cardiovascular magnetic resonance measurements.

BACKGROUND: Right atrial (RA) area predicts mortality in patients with pulmonary hypertension, and i...

Prediction of hypertension using traditional regression and machine learning models: A systematic review and meta-analysis.

OBJECTIVE: We aimed to identify existing hypertension risk prediction models developed using traditi...

Expert-augmented automated machine learning optimizes hemodynamic predictors of spinal cord injury outcome.

Artificial intelligence and machine learning (AI/ML) is becoming increasingly more accessible to bio...

Identification of Characteristic Points in Multivariate Physiological Signals by Sensor Fusion and Multi-Task Deep Networks.

Identification of characteristic points in physiological signals, such as the peak of the R wave in ...

Deep Learning-Based Electrocardiograph in Evaluating Radiofrequency Ablation for Rapid Arrhythmia.

This study is aimed at analyzing the important role of deep learning-based electrocardiograph (ECG) ...

An imaging-based artificial intelligence model for non-invasive grading of hepatic venous pressure gradient in cirrhotic portal hypertension.

The hepatic venous pressure gradient (HVPG) is the gold standard for cirrhotic portal hypertension (...

Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement.

Continuous blood pressure (BP) measurement is crucial for long-term cardiovascular monitoring, espec...

TIMP-1: A Circulating Biomarker for Pulmonary Hypertension Diagnosis Among Chronic Obstructive Pulmonary Disease Patients.

Pulmonary hypertension (PH) is a common complication of chronic obstructive pulmonary disease (COPD)...

Effectiveness of Artificial Intelligence Models for Cardiovascular Disease Prediction: Network Meta-Analysis.

Heart failure is the most common cause of death in both males and females around the world. Cardiova...

Predicting adverse cardiac events in sarcoidosis: deep learning from automated characterization of regional myocardial remodeling.

Recognizing early cardiac sarcoidosis (CS) imaging phenotypes can help identify opportunities for ef...

Artificial Intelligence Detection of Left Ventricular Systolic Dysfunction Using Chest X-Rays: Prospective Validation, Please.