Congestive Heart Failure

Soft robotic patient-specific hydrodynamic model of aortic stenosis and ventricular remodeling.

Aortic stenosis (AS) affects about 1.5 million people in the United States and is associated with a ...

Dyspnea Severity Assessment Based on Vocalization Behavior with Deep Learning on the Telephone.

In this paper, a system to assess dyspnea with the mMRC scale, on the phone, via deep learning, is p...

Phonocardiogram transfer learning-based CatBoost model for diastolic dysfunction identification using multiple domain-specific deep feature fusion.

Left ventricular diastolic dyfunction detection is particularly important in cardiac function screen...

Segmentation of the aorta in systolic phase from 4D flow MRI: multi-atlas vs. deep learning.

OBJECTIVE: In the management of the aortic aneurysm, 4D flow magnetic resonance Imaging provides val...

Deep learning automates bidimensional and volumetric tumor burden measurement from MRI in pre- and post-operative glioblastoma patients.

Tumor burden assessment by magnetic resonance imaging (MRI) is central to the evaluation of treatmen...

Deep learning-based diagnosis of feline hypertrophic cardiomyopathy.

Feline hypertrophic cardiomyopathy (HCM) is a common heart disease affecting 10-15% of all cats. Cat...

The predictive value of deep learning-based cardiac ultrasound flow imaging for hypertrophic cardiomyopathy complicating arrhythmias.

OBJECTIVE: To investigate the predictive value of deep learning-based cardiac ultrasound flow imagin...

NVTrans-UNet: Neighborhood vision transformer based U-Net for multi-modal cardiac MR image segmentation.

With the rapid development of artificial intelligence and image processing technology, medical imagi...

Reliability of respiratory-gated real-time two-dimensional cine incorporating deep learning reconstruction for the assessment of ventricular function in an adult population.

This study aimed to assess the image quality and accuracy of respiratory-gated real-time two-dimensi...

An end-end deep learning framework for lesion segmentation on multi-contrast MR images-an exploratory study in a rat model of traumatic brain injury.

Traumatic brain injury (TBI) engenders traumatic necrosis and penumbra-areas of secondary neural inj...

A deep learning framework assisted echocardiography with diagnosis, lesion localization, phenogrouping heterogeneous disease, and anomaly detection.

Echocardiography is the first-line diagnostic technique for heart diseases. Although artificial inte...

A deep learning platform to assess drug proarrhythmia risk.

Drug safety initiatives have endorsed human iPSC-derived cardiomyocytes (hiPSC-CMs) as an in vitro m...

Robotic Redo Mitral Valve Replacement and Atrioventricular Groove Pseudoaneurysm Repair.

We report the use of robot-assisted right thoracotomy in the management of a patient who presented w...

A machine learning approach for predicting perihematomal edema expansion in patients with intracerebral hemorrhage.

OBJECTIVES: Preventing the expansion of perihematomal edema (PHE) represents a novel strategy for th...

Aortic Distensibility Measured by Automated Analysis of Magnetic Resonance Imaging Predicts Adverse Cardiovascular Events in UK Biobank.

Background Automated analysis of cardiovascular magnetic resonance images provides the potential to ...

Research on Assistant Diagnosis of Fundus Optic Neuropathy Based on Deep Learning.

PURPOSE: The purpose of this study was to use the neural network to distinguish optic edema (ODE), a...

Natural language processing for identification of hypertrophic cardiomyopathy patients from cardiac magnetic resonance reports.

BACKGROUND: Cardiac magnetic resonance (CMR) imaging is important for diagnosis and risk stratificat...

Multimodal data for systolic and diastolic blood pressure prediction: The hypertension conscious artificial intelligence.

Cardiovascular Imaging in China: Yesterday, Today, and Tomorrow.

The high prevalence and mortality of cardiovascular diseases in China's large population has increas...

Artificial Intelligence Applied to Cardiomyopathies: Is It Time for Clinical Application?

PURPOSE OF REVIEW: Artificial intelligence (AI) techniques have the potential to remarkably change t...

Bridging the resources gap: deep learning for fluorescein angiography and optical coherence tomography macular thickness map image translation.

BACKGROUND: To assess the ability of the pix2pix generative adversarial network (pix2pix GAN) to syn...