Latest AI and machine learning research in hypertension for healthcare professionals.
AIMS: This study aimed to evaluate ventricular diastolic properties using three-dimensional echocardiography and tissue Doppler imaging at rest and during exercise in heart failure with preserved ejection fraction (HFpEF) patients with borderline evidence of diastolic dysfunction at rest.
The aim of this study was to verify the measurement concordance of cardiac index (CI), extra-vascular lung water index (EVLWI) and global end diastolic volume index (GEDVI) with transpulmonary thermodilution (TPTD) between the jugular and femoral access with catheters inserted ipsilaterally in critically ill burn patients. Correlations were excellent and the concordance was good for the CI, EVLW a...
BACKGROUND: Heart rate variability (HRV) has been widely used in the non-invasive evaluation of cardiovascular function. Recent studies have also atta...
Heart disease is the leading cause of death globally and a significant part of the human population lives with it. A number of risk factors have been ...
Vitamin D deficiency is a common health problem in Saudi Arabia especially in children and adolescents. Many studies have reported the relation betwee...
AIMS/INTRODUCTION: The changes in metabolic parameters in type 2 diabetic patients who fast during Ramadan have not been studied in Singapore. This st...
This paper presents a novel method for discrimination between innocent and pathological murmurs using the growing time support vector machine (GTSVM)....
BACKGROUND: To develop and assess an efficient method to identify end-expiratory end-diastolic (ED) and end-systolic (ES) images for accurate quantifi...
BACKGROUND: The diagnostic performance of biochemical scores and artificial neural network models for portal hypertension and cirrhosis is not well es...
Rats have been used extensively as animal models to study physiological and pathological processes involved in human diseases. Numerous rat strains ha...
The spectrum of EEG has been studied to predict the depth of anesthesia using variety of signal processing methods up to date. Those standard models h...
Background: Unstructured biomedical data, such as echocardiography reports, are rich in information but time consuming to analyze at scale. Rule-based...
Inadequate blood pressure (BP) monitoring and management outside of clinical settings can worsen major cardiovascular risk factors such as hypertensio...
Wearable electrocardiogram (ECG) and photoplethysmogram (PPG) sensors are complementary but individually fragile: motion artifact, poor contact, and s...
Objective. To develop and evaluate a cuffless continuous blood pressure (BP) estimator using temporal physiological and demographic features. We propo...
Background: Right ventricular (RV) function predicts survival in pulmonary hypertension (PH) and other cardiovascular diseases, yet echocardiographic ...
Abstract Background: Cardiovascular-kidney-metabolic (CKM) syndrome is an increasingly prevalent multisystem condition associated with morbidity, frag...
Importance: Consumer wearables such as the Apple Watch can record single-lead electrocardiograms (ECGs) but are used mainly to detect rhythm disorders...
Deep learning models for neuroimaging have largely been developed for individual tasks, limiting knowledge transfer across applications. Here we intro...
Background: White matter hyperintensities (WMH) represent the most visible manifestation of cerebral small vessel disease and of white matter patholog...