Congestive Heart Failure

Automated identification and quantification of metastatic brain tumors and perilesional edema based on a deep learning neural network.

PURPOSE: This paper presents a deep learning model for use in the automated segmentation of metastatic brain tumors and associated perilesional edema.

The Role of Serum NT-proBNP for Predicting Left Ventricular Systolic Dysfunction in Hospitalized Patients in Sri Lanka.

BACKGROUND/AIMS: Only a few studies have addressed the role of NT-proBNP in identifying Left Ventricular Systolic Dysfunction (LVSD) in South Asian populations. Therefore, the current study was aimed at assessing the use of serum NT-proBNP in predicting LVSD in a hospitalized population in Sri Lanka.

Artificial intelligence-based identification of left ventricular systolic dysfunction from 12-lead electrocardiograms: external validation and advanced application of an existing model.

AIMS: The diagnostic application of artificial intelligence (AI)-based models to detect cardiovascular diseases from electrocardiograms (ECGs) evolves...

Accuracy of Integrated Artificial Intelligence Grading Using Handheld Retinal Imaging in a Community Diabetic Eye Screening Program.

PURPOSE: To evaluate mydriatic handheld retinal imaging performance assessed by point-of-care (POC) artificial intelligence (AI) as compared with reti...

Artificial intelligence-enhanced electrocardiogram for arrhythmogenic right ventricular cardiomyopathy detection.

AIMS: ECG abnormalities are often the first signs of arrhythmogenic right ventricular cardiomyopathy (ARVC) and we hypothesized that an artificial int...

EstimATTR: A Simplified, Machine-Learning-Based Tool to Predict the Risk of Wild-Type Transthyretin Amyloid Cardiomyopathy.

BACKGROUND: Wild-type transthyretin amyloid cardiomyopathy (ATTRwt-CM), an increasingly recognized cause of heart failure (HF), often remains undiagno...

Fixed, Dilated, and Cannulated - Medical Management of Elevated Intracranial Pressures due to a Large Intracranial Hemorrhage in a Patient on Veno-Venous Extracorporeal Membrane Oxygenation: Case Report.

A 40-year-old woman presented with mediastinitis, necrotizing pancreatitis, and severe acute respiratory distress syndrome with refractory acidemia (p...

A comprehensive review of applications of artificial intelligence in echocardiography.

Echocardiography plays a crucial role in diagnosis of cardiovascular diseases. Artificial intelligence has emerged as a high-precision tool to automat...

Hypotensive and Endothelium-Dependent Vasorelaxant Effects of Grayblue Spicebush Ethanol Extract in Rats.

Hypertension is one of the most common chronic diseases, and its prevalence is increasing worldwide. (Siebold & Zucc.) Blume, known as grayblue spice...

Clinical service evaluation of the feasibility and reproducibility of novel artificial intelligence based-echocardiographic quantification of global longitudinal strain and left ventricular ejection fraction in trastuzumab-treated patients.

INTRODUCTION: Cardiotoxicity is a potential prognostically important complication of certain chemotherapeutic agents that may result in preclinical or...

Echocardiography-Based Deep Learning Model to Differentiate Constrictive Pericarditis and Restrictive Cardiomyopathy.

BACKGROUND: Constrictive pericarditis (CP) is an uncommon but reversible cause of diastolic heart failure if appropriately identified and treated. How...

Electrocardiogram-based deep learning model to screen peripartum cardiomyopathy.

BACKGROUND: Peripartum cardiomyopathy, one of the most fatal conditions during delivery, results in heart failure secondary to left ventricular systol...

Efficacy and Safety of Chinese Herbal Medicine in Patients with Acute Intracerebral Hemorrhage: Protocol for a Randomized Placebo-Controlled Double-Blinded Multicenter Trial.

INTRODUCTION: The popular traditional Chinese medicine (TCM) compound FYTF-919 (Zhong Feng Xing Nao prescription) may improve outcome from acute intra...

Real-time dual prediction of intradialytic hypotension and hypertension using an explainable deep learning model.

Both intradialytic hypotension (IDH) and hypertension (IDHTN) are associated with poor outcomes in hemodialysis patients, but a model predicting dual ...

Deep Learning Algorithms to Detect Murmurs Associated With Structural Heart Disease.

Background The success of cardiac auscultation varies widely among medical professionals, which can lead to missed treatments for structural heart dis...

Automatic Quantification of COVID-19 Pulmonary Edema by Self-supervised Contrastive Learning.

We proposed a self-supervised machine learning method to automatically rate the severity of pulmonary edema in the frontal chest X-ray radiographs (CX...

Probabilistic Modeling for Image Registration Using Radial Basis Functions: Application to Cardiac Motion Estimation.

Cardiovascular diseases (CVDs) are the leading cause of death, affecting the cardiac dynamics over the cardiac cycle. Estimation of cardiac motion pla...

Blood pressure estimation and classification using a reference signal-less photoplethysmography signal: a deep learning framework.

The markers that help to predict th function of a cardiovascular system are hemodynamic parameters like blood pressure (BP), stroke volume, heart rate...

Editorial for "Deep Learning for Discrimination of Hypertrophic Cardiomyopathy and Hypertensive Heart Disease on MRI Native T1 Maps".

Heterogeneous treatment effects of coronary artery bypass grafting in ischemic cardiomyopathy: A machine learning causal forest analysis.

OBJECTIVES: We aim to evaluate the heterogeneous treatment effects of coronary artery bypass grafting in patients with ischemic cardiomyopathy and to ...