Cardiovascular

Artificial Intelligence in Cardiovascular Care-Part 2: Applications: JACC Review Topic of the Week.

Recent artificial intelligence (AI) advancements in cardiovascular care offer potential enhancements...

Successful prediction of left bundle branch block-induced cardiomyopathy and treatment effect by artificial intelligence-enabled electrocardiogram.

BACKGROUND: Left bundle branch block (LBBB) induced cardiomyopathy is an increasingly recognized dis...

Predicting ischemic stroke patients' prognosis changes using machine learning in a nationwide stroke registry.

Accurately predicting the prognosis of ischemic stroke patients after discharge is crucial for physi...

Automated detection of myocardial infarction based on an improved state refinement module for LSTM/GRU.

Myocardial infarction (MI) is a common cardiovascular disease caused by the blockages of coronary ar...

Leveraging Artificial Intelligence to Optimize the Care of Peripheral Artery Disease Patients.

Peripheral artery disease is a major atherosclerotic disease that is associated with poor outcomes s...

Deep learning-based rapid image reconstruction and motion correction for high-resolution cartesian first-pass myocardial perfusion imaging at 3T.

PURPOSE: To develop and evaluate a deep learning (DL) -based rapid image reconstruction and motion c...

Deep learning supported echocardiogram analysis: A comprehensive review.

An echocardiogram is a sophisticated ultrasound imaging technique employed to diagnose heart conditi...

AcquisitionFocus: Joint Optimization of Acquisition Orientation and Cardiac Volume Reconstruction Using Deep Learning.

In cardiac cine imaging, acquiring high-quality data is challenging and time-consuming due to the ar...

Ethical use of artificial intelligence to prevent sudden cardiac death: an interview study of patient perspectives.

BACKGROUND: The emergence of artificial intelligence (AI) in medicine has prompted the development o...

Identification of Congenital Valvular Murmurs in Young Patients Using Deep Learning-Based Attention Transformers and Phonocardiograms.

One in every four newborns suffers from congenital heart disease (CHD) that causes defects in the he...

Deep Learning for Automated Measurement of Total Cardiac Volume for Heart Transplantation Size Matching.

Total Cardiac Volume (TCV)-based size matching using Computed Tomography (CT) is a novel technique t...

Prediction of adverse cardiovascular events in children using artificial intelligence-based electrocardiogram.

BACKGROUND: Convolutional neural networks (CNNs) have emerged as a novel method for evaluating heart...

New era in right ventricular imaging with AI: Challenges and horizons.

Machine learning identifies novel coagulation genes as diagnostic and immunological biomarkers in ischemic stroke.

BACKGROUND: Coagulation system is currently known associated with the development of ischemic stroke...

AttGRU-HMSI: enhancing heart disease diagnosis using hybrid deep learning approach.

Heart disease is a major global cause of mortality and a major public health problem for a large num...

Prostatic Fossa Pseudoaneurysm After Robot-Assisted Radical Prostatectomy (RARP): A Case Report.

BACKGROUND RARP is an established procedure in treatment of localized prostate cancer. Hemorrhagic c...

Robot-assisted support combined with electrical stimulation for the lower extremity in stroke patients: a systematic review.

. The incidence of stroke rising, leading to an increased demand for rehabilitation services. Litera...

DeepMesh: Mesh-Based Cardiac Motion Tracking Using Deep Learning.

3D motion estimation from cine cardiac magnetic resonance (CMR) images is important for the assessme...

Automated cardiac arrhythmia detection techniques: a comprehensive review for prospective approach.

Abnormal cardiac functionality produces irregular heart rhythms which are commonly known as arrhythm...

Transcatheter Aortic Valve Replacement and Coronary Protection Guided by Deep Learning and 3-Dimensional Printing.

OBJECTIVE: In this case report, the auxiliary role of deep learning and 3-dimensional printing techn...

Machine learning model based on RCA-PDCA nursing methods and differentiating factors to predict hypotension during cesarean section surgery.

BACKGROUND: Intraoperative hypotension during cesarean section has become a serious complication for...