Hypertension

A Novel Automated Blood Pressure Estimation Algorithm Using Sequences of Korotkoff Sounds.

The use of automated non-invasive blood pressure (NIBP) measurement devices is growing, as they can ...

Artificial Intelligence in Hypertension: Seeing Through a Glass Darkly.

Hypertension remains the largest modifiable cause of mortality worldwide despite the availability of...

Two novel potent ACEI peptides isolated from meat hydrolysates using analysis: identification, screening and inhibitory mechanisms.

The aim of this study was to discover potent angiotensin-converting enzyme (ACE) inhibitory (ACEI) p...

Blood Pressure Morphology Assessment from Photoplethysmogram and Demographic Information Using Deep Learning with Attention Mechanism.

Arterial blood pressure (ABP) is an important vital sign from which it can be extracted valuable inf...

Assessment of Thoracic Pain Using Machine Learning: A Case Study from Baja California, Mexico.

Thoracic pain is a shared symptom among gastrointestinal diseases, muscle pain, emotional disorders,...

Artificial Intelligence and Left Ventricular Diastolic Function Assessment: A New Tool for Improved Practice?

A deep learning methodology for the automated detection of end-diastolic frames in intravascular ultrasound images.

Coronary luminal dimensions change during the cardiac cycle. However, contemporary volumetric intrav...

A deep-learning semantic segmentation approach to fully automated MRI-based left-ventricular deformation analysis in cardiotoxicity.

Left-ventricular (LV) strain measurements with the Displacement Encoding with Stimulated Echoes (DEN...

Risk factors analysis of COVID-19 patients with ARDS and prediction based on machine learning.

COVID-19 is a newly emerging infectious disease, which is generally susceptible to human beings and ...

Physical Features and Vital Signs Predict Serum Albumin and Globulin Concentrations Using Machine Learning.

OBJECTIVE: Serum protein concentrations are diagnostically and prognostically valuable in cancer and...

Associated factors of white matter hyperintensity volume: a machine-learning approach.

To identify the most important parameters associated with cerebral white matter hyperintensities (WM...

Prediction of death status on the course of treatment in SARS-COV-2 patients with deep learning and machine learning methods.

BACKGROUND AND OBJECTIVE: The new type of Coronavirus (2019-nCov) epidemic spread rapidly, causing m...

Retraining Convolutional Neural Networks for Specialized Cardiovascular Imaging Tasks: Lessons from Tetralogy of Fallot.

Ventricular contouring of cardiac magnetic resonance imaging is the gold standard for volumetric ana...

External validation of a deep learning electrocardiogram algorithm to detect ventricular dysfunction.

OBJECTIVE: To validate a novel artificial-intelligence electrocardiogram algorithm (AI-ECG) to detec...

Learning fine-grained estimation of physiological states from coarse-grained labels by distribution restoration.

Due to its importance in clinical science, the estimation of physiological states (e.g., the severit...

Automatic recognition of murmurs of ventricular septal defect using convolutional recurrent neural networks with temporal attentive pooling.

Recognizing specific heart sound patterns is important for the diagnosis of structural heart disease...

LU-Net: A Multistage Attention Network to Improve the Robustness of Segmentation of Left Ventricular Structures in 2-D Echocardiography.

Segmentation of cardiac structures is one of the fundamental steps to estimate volumetric indices of...

Prediction of response to cardiac resynchronization therapy using a multi-feature learning method.

We hypothesized that a multiparametric evaluation, based on the combination of electrocardiographic ...

Deep learning to predict elevated pulmonary artery pressure in patients with suspected pulmonary hypertension using standard chest X ray.

Accurate diagnosis of pulmonary hypertension (PH) is crucial to ensure that patients receive timely ...

Using the National Trauma Data Bank (NTDB) and machine learning to predict trauma patient mortality at admission.

A 400-estimator gradient boosting classifier was trained to predict survival probabilities of trauma...

Effect of Chronotherapy of Antihypertensives in Chronic Kidney Disease: A Randomized Control Trial.

INTRODUCTION: There is a higher prevalence of non-dipping pattern in hypertensive chronic kidney dis...