Hypertension

Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement.

Continuous blood pressure (BP) measurement is crucial for long-term cardiovascular monitoring, especially for prompt hypertension detection. However, most of the continuous BP measurements rely on the pulse transit time (PTT) from multiple-channel physiological acquisition systems that impede wearable applications. Recently, wearable and smart health electronics have become significant for next-ge...

TIMP-1: A Circulating Biomarker for Pulmonary Hypertension Diagnosis Among Chronic Obstructive Pulmonary Disease Patients.

Pulmonary hypertension (PH) is a common complication of chronic obstructive pulmonary disease (COPD) and induces increased mortality among COPD patients. However, there are no blood biomarkers to identify PH in COPD. Here, we investigated whether circulating angiogenic factors and cytokines could serve as (a) biomarker (s) for COPD-PH patients. Using Angiogenesis and Cytokine proteome profile arra...

Effectiveness of Artificial Intelligence Models for Cardiovascular Disease Prediction: Network Meta-Analysis.

Heart failure is the most common cause of death in both males and females around the world. Cardiovascular diseases (CVDs), in particular, are the mai...

Predicting adverse cardiac events in sarcoidosis: deep learning from automated characterization of regional myocardial remodeling.

Recognizing early cardiac sarcoidosis (CS) imaging phenotypes can help identify opportunities for effective treatment before irreversible myocardial p...

Artificial Intelligence Detection of Left Ventricular Systolic Dysfunction Using Chest X-Rays: Prospective Validation, Please.

Improving robustness of automatic cardiac function quantification from cine magnetic resonance imaging using synthetic image data.

Although having been the subject of intense research over the years, cardiac function quantification from MRI is still not a fully automatic process i...

Machine Learning Techniques in Blood Pressure Management During the Acute Phase of Ischemic Stroke.

BACKGROUND AND PURPOSE: Elevated blood pressure (BP) in acute ischemic stroke is common. A raised BP is related to mortality and disability, yet exces...

Machine learning-based diagnosis and risk factor analysis of cardiocerebrovascular disease based on KNHANES.

The prevalence of cardiocerebrovascular disease (CVD) is continuously increasing, and it is the leading cause of human death. Since it is difficult fo...

Iron Deficiency Impacts Diastolic Function, Aerobic Exercise Capacity, and Patient Phenotyping in Heart Failure With Preserved Ejection Fraction: A Subanalysis of the OptimEx-Clin Study.

AIMS: Iron deficiency (ID) is linked to reduced aerobic exercise capacity and poor prognosis in patients with heart failure (HF) with reduced ejection...

Automated In-Line Artificial Intelligence Measured Global Longitudinal Shortening and Mitral Annular Plane Systolic Excursion: Reproducibility and Prognostic Significance.

Background Global longitudinal shortening (GL-Shortening) and the mitral annular plane systolic excursion (MAPSE) are known markers in heart failure p...

Effects of age, gender, and hemisphere on cerebrovascular hemodynamics in children and young adults: Developmental scores and machine learning classifiers.

A constant blood supply to the brain is required for mental function. Research with Doppler ultrasonography has important clinical value and burgeonin...

The Design of Adolescents' Physical Health Prediction System Based on Deep Reinforcement Learning.

According to the general recognition in the first half of the last century, hypertension was not considered a kind of disease, but was regarded as a c...

Analysis of Clinical Parameters, Drug Consumption and Use of Health Resources in a Southern European Population with Alcohol Abuse Disorder during COVID-19 Pandemic.

The disruption in healthcare attention to people with alcohol dependence, along with psychological decompensation as a consequence of lockdown derived...

Development, validation, and application of a machine learning model to estimate salt consumption in 54 countries.

Global targets to reduce salt intake have been proposed, but their monitoring is challenged by the lack of population-based data on salt consumption. ...

Application of ensemble machine learning algorithms on lifestyle factors and wearables for cardiovascular risk prediction.

This study looked at novel data sources for cardiovascular risk prediction including detailed lifestyle questionnaire and continuous blood pressure mo...

Ultrasound Image-Guided Nerve Block Combined with General Anesthesia under an Artificial Intelligence Algorithm on Patients Undergoing Radical Gastrectomy for Gastric Cancer during and after Operation.

This study was aimed at investigating the location of gastric cancer by using a gastroscope image based on an artificial intelligence algorithm for ga...

Cardiovascular disease detection using machine learning and carotid/femoral arterial imaging frameworks in rheumatoid arthritis patients.

The study proposes a novel machine learning (ML) paradigm for cardiovascular disease (CVD) detection in individuals at medium to high cardiovascular r...

Soft Transducer for Patient's Vitals Telemonitoring with Deep Learning-Based Personalized Anomaly Detection.

This work addresses the design, development and implementation of a 4.0-based wearable soft transducer for patient-centered vitals telemonitoring. In ...

Rhabdomyolysis: An evidence-based approach.

A 76-year-old lady was found on the floor following a fall at home. She was uninjured, but unable to get up, and had been lying on the floor for rough...

Deep learning-based whole-heart segmentation in 4D contrast-enhanced cardiac CT.

Automatic cardiac chamber and left ventricular (LV) myocardium segmentation over the cardiac cycle significantly extends the utilization of contrast-e...