Hypertension

Minimally invasive monitor of cardiac output based on the machine-learning analysis of the pulse contour of the peripheral arterial pressure.

In the hemodynamic management of anesthetized patients during surgical operation, minimally invasive...

Deep Learning for identifying systolic complexes in SCG traces: a cross-dataset analysis.

The seismocardiographic signal is a promising alternative to the traditional ECG in the analysis of ...

Dissecting unique and common variance across body and brain health indicators using age prediction.

Ageing is a heterogeneous multisystem process involving different rates of decline in physiological ...

Deep learning to assess right ventricular ejection fraction from two-dimensional echocardiograms in precapillary pulmonary hypertension.

BACKGROUND: Precapillary pulmonary hypertension (PH) is characterized by a sustained increase in rig...

Better Blood Pressure Control for Stroke Patients in the ICU: A Deep Reinforcement Learning with Supervised Guidance Approach for Adaptive Infusion Rate Tuning.

Blood pressure variability (BPV) plays a critical role in vascular diseases, particularly in acute i...

Comparison of machine learning models to predict complications of bariatric surgery: A systematic review.

Due to changes in lifestyle, bariatric surgery is expanding worldwide. However, this surgery has nu...

Advanced Machine Learning Models for Predicting Post-Thrombolysis Hemorrhagic Transformation in Acute Ischemic Stroke Patients: A Systematic Review and Meta-Analysis.

Thrombolytic therapy is essential for acute ischemic stroke (AIS) management but poses a risk of he...

Fine grained automatic left ventricle segmentation via ROI based Tri-Convolutional neural networks.

BACKGROUND: The left ventricle segmentation (LVS) is crucial to the assessment of cardiac function. ...

Multimodality Risk Assessment of Patients with Ischemic Heart Disease Using Deep Learning Models Applied to Electrocardiograms and Chest X-rays.

Comprehensive management approaches for patients with ischemic heart disease (IHD) are important aid...

A Deep Learning Pipeline for Assessing Ventricular Volumes from a Cardiac MRI Registry of Patients with Single Ventricle Physiology.

Purpose To develop an end-to-end deep learning (DL) pipeline for automated ventricular segmentation ...

HTNpedia: A Knowledge Base for Hypertension Research.

BACKGROUND: Hypertension is notably a serious public health concern due to its high prevalence and s...

Antihypertensive prescribing patterns in non-dialysis dependent chronic kidney disease: Findings from the Salford Kidney Study.

BACKGROUND: Hypertension is commonly observed in patients living with chronic kidney disease (CKD). ...

DETERMINATION OF THE PRA POSITIVITY PERCENTAGE IN MALE PATIENTS WITH CHRONIC KIDNEY DISEASE BY USING FLOW CYTOMETRY TECHNIQUE.

The antibodies directed against human leukocyte antigen (HLA) molecules, which play a crucial role i...

Demographic Information Fusion Using Attentive Pooling In CNN-GRU Model For Systolic Blood Pressure Estimation.

Fusing demographic information into deep learning models has become of interest in recent end-to-end...

Hepatic Hydrothorax Without Ascites: A Diagnostic And Management Challenge.

Hepatic hydrothorax refers to the presence of a pleural effusion (usually >500 mL) in a patient with...

[A deep-learning model for the assessment of coronary heart disease and related risk factors via the evaluation of retinal fundus photographs].

To develop and validate a deep learning model based on fundus photos for the identification of coro...

Clinician Adoption of an Artificial Intelligence Algorithm to Detect Left Ventricular Systolic Dysfunction in Primary Care.

OBJECTIVE: To compare the clinicians' characteristics of "high adopters" and "low adopters" of an ar...

Using deep learning to diagnose pulmonary hypertension.

A framework of deep learning networks provides expert-level accuracy for the detection and prognostication of pulmonary arterial hypertension.

AIMS: To test the hypothesis that deep learning (DL) networks reliably detect pulmonary arterial hyp...

Estimation of left ventricular parameters based on deep learning method.

Estimating material properties of personalized human left ventricular (LV) modelling is a central pr...

Detecting Glaucoma in the Ocular Hypertension Study Using Deep Learning.

IMPORTANCE: Automated deep learning (DL) analyses of fundus photographs potentially can reduce the c...