Cardiovascular

Hypertension

Latest AI and machine learning research in hypertension for healthcare professionals.

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Analyzing brain structural differences associated with categories of blood pressure in adults using empirical kernel mapping-based kernel ELM.

BACKGROUND: Hypertension increases the risk of angiocardiopathy and cognitive disorder. Blood pressu...

Estimation of Arterial Blood Pressure Based on Artificial Intelligence Using Single Earlobe Photoplethysmography during Cardiopulmonary Resuscitation.

This study investigates the feasibility of estimation of blood pressure (BP) using a single earlobe ...

Highly precise risk prediction model for new-onset hypertension using artificial intelligence techniques.

Hypertension is a significant public health issue. The ability to predict the risk of developing hyp...

Pulse Wave Velocity and Machine Learning to Predict Cardiovascular Outcomes in Prediabetic and Diabetic Populations.

Few studies have addressed the predictive value of arterial stiffness determined by pulse wave veloc...

A novel computer-aided diagnosis system for the early detection of hypertension based on cerebrovascular alterations.

Hypertension is a leading cause of mortality in the USA. While simple tools such as the sphygmomanom...

A machine learning approach for the prediction of pulmonary hypertension.

BACKGROUND: Machine learning (ML) is a powerful tool for identifying and structuring several informa...

Machine Learning to Predict In-Hospital Morbidity and Mortality after Traumatic Brain Injury.

Recently, successful predictions using machine learning (ML) algorithms have been reported in variou...

Prediction model development of late-onset preeclampsia using machine learning-based methods.

Preeclampsia is one of the leading causes of maternal and fetal morbidity and mortality. Due to the ...

SVR ensemble-based continuous blood pressure prediction using multi-channel photoplethysmogram.

In this paper, a continuous non-occluding blood pressure (BP) prediction method is proposed using mu...

On the interpretability of machine learning-based model for predicting hypertension.

BACKGROUND: Although complex machine learning models are commonly outperforming the traditional simp...

An Automatic Approach Using ELM Classifier for HFpEF Identification Based on Heart Sound Characteristics.

Heart failure with preserved ejection fraction (HFpEF) is a complex and heterogeneous clinical syndr...

Prediction of Aneurysm Stability Using a Machine Learning Model Based on PyRadiomics-Derived Morphological Features.

Background and Purpose- Discrimination of the stability of intracranial aneurysms is critical for de...

Fibroblast growth factor 23 and tubular sodium handling in young patients with incipient chronic kidney disease.

BACKGROUND: Experimental studies have shown fibroblast growth factor 23 FGF23)-mediated upregulation...

Identifying pre-disease signals before metabolic syndrome in mice by dynamical network biomarkers.

The establishment of new therapeutic strategies for metabolic syndrome is urgently needed because me...

A Non-Invasive Continuous Blood Pressure Estimation Approach Based on Machine Learning.

Considering the existing issues of traditional blood pressure (BP) measurement methods and non-invas...

Prediction of Nephropathy in Type 2 Diabetes: An Analysis of the ACCORD Trial Applying Machine Learning Techniques.

Applying data mining and machine learning (ML) techniques to clinical data might identify predictive...

A Precision Environment-Wide Association Study of Hypertension via Supervised Cadre Models.

We consider the problem in precision health of grouping people into subpopulations based on their de...

Statistical Approaches Based on Deep Learning Regression for Verification of Normality of Blood Pressure Estimates.

Oscillometric blood pressure (BP) monitors currently estimate a single point but do not identify var...

An Efficient Cardiac Arrhythmia Onset Detection Technique Using a Novel Feature Rank Score Algorithm.

The interpretation of various cardiovascular blood flow abnormalities can be identified using Electr...

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