Hypertension

Imputation of the continuous arterial line blood pressure waveform from non-invasive measurements using deep learning.

In two-thirds of intensive care unit (ICU) patients and 90% of surgical patients, arterial blood pre...

How to standardize the measurement of left ventricular ejection fraction.

Despite recent advances in imaging for myocardial deformation, left ventricular ejection fraction (L...

PEDF, a pleiotropic WTC-LI biomarker: Machine learning biomarker identification and validation.

Biomarkers predict World Trade Center-Lung Injury (WTC-LI); however, there remains unaddressed multi...

Using Wearables and Machine Learning to Enable Personalized Lifestyle Recommendations to Improve Blood Pressure.

Blood pressure (BP) is an essential indicator for human health and is known to be greatly influence...

Can Machine Learning Help Simplify the Measurement of Diastolic Function in Echocardiography?

Phenogrouping Diastolic Dysfunction by Artificial Intelligence: Learning From What We Teach the Machines.

Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology.

BACKGROUND AND OBJECTIVE: Magnetic resonance imaging is the most reliable imaging technique to asses...

The effect of cardiac rhythm on artificial intelligence-enabled ECG evaluation of left ventricular ejection fraction prediction in cardiac intensive care unit patients.

The presence of left ventricular systolic dysfunction (LVSD) alters clinical management and prognosi...

Effect of age and sex on fully automated deep learning assessment of left ventricular function, volumes, and contours in cardiac magnetic resonance imaging.

Deep learning algorithms for left ventricle (LV) segmentation are prone to bias towards the training...

Combined deep CNN-LSTM network-based multitasking learning architecture for noninvasive continuous blood pressure estimation using difference in ECG-PPG features.

The pulse arrival time (PAT), the difference between the R-peak time of electrocardiogram (ECG) sign...

Artificial Intelligence-Augmented Electrocardiogram Detection of Left Ventricular Systolic Dysfunction in the General Population.

OBJECTIVE: To validate an artificial intelligence-augmented electrocardiogram (AI-ECG) algorithm for...

Blood Biomarkers Predict Cardiac Workload Using Machine Learning.

INTRODUCTION: Rate pressure product (the product of heart rate and systolic blood pressure) is a mea...

Tinnitus Frequency is Higher in Patients with Chronic Heart Failure with Reduced Ejection Fraction and is Closely Related to NT-proBNP Level.

There is not enough information about tinnitus and related parameters in patients with heart failure...

Health improvement framework for actionable treatment planning using a surrogate Bayesian model.

Clinical decision-making regarding treatments based on personal characteristics leads to effective h...

Classification and Prediction on the Effects of Nutritional Intake on Overweight/Obesity, Dyslipidemia, Hypertension and Type 2 Diabetes Mellitus Using Deep Learning Model: 4-7th Korea National Health and Nutrition Examination Survey.

Few studies have been conducted to classify and predict the influence of nutritional intake on overw...

Deep-Learning Models for the Echocardiographic Assessment of Diastolic Dysfunction.

OBJECTIVES: The authors explored a deep neural network (DeepNN) model that integrates multidimension...

Prediction of premature all-cause mortality in patients receiving peritoneal dialysis using modified artificial neural networks.

Premature all-cause mortality is high in patients receiving peritoneal dialysis (PD). The accurate a...

Prediction of brain age from routine T2-weighted spin-echo brain magnetic resonance images with a deep convolutional neural network.

Our study investigated the feasibility and clinical relevance of brain age prediction using axial T2...

Machine learning algorithm for characterizing risks of hypertension, at an early stage in Bangladesh.

BACKGROUND AND AIMS: Hypertension has become a major public health issue as the prevalence and risk ...

Using CNN and HHT to Predict Blood Pressure Level Based on Photoplethysmography and Its Derivatives.

According to the WTO, there were 1.13 billion hypertension patients worldwide in 2015. The WTO encou...

Multibeat echocardiographic phase detection using deep neural networks.

BACKGROUND: Accurate identification of end-diastolic and end-systolic frames in echocardiographic ci...