AI Medical Compendium Journal:
Echocardiography (Mount Kisco, N.Y.)

Showing 1 to 10 of 16 articles

An attention-based deep learning method for right ventricular quantification using 2D echocardiography: Feasibility and accuracy.

Echocardiography (Mount Kisco, N.Y.)
AIM: To test the feasibility and accuracy of a new attention-based deep learning (DL) method for right ventricular (RV) quantification using 2D echocardiography (2DE) with cardiac magnetic resonance imaging (CMR) as reference.

Artificial intelligence for automated evaluation of aortic measurements in 2D echocardiography: Feasibility, accuracy, and reproducibility.

Echocardiography (Mount Kisco, N.Y.)
AIMS: This study sought to examine the feasibility, accuracy and reproducibility of a novel, fully automated 2D transthoracic echocardiography (2D TTE) parasternal long axis (PLAX) view aortic measurements quantification software compared to board-ce...

Artificial intelligence in echocardiography: Review and limitations including epistemological concerns.

Echocardiography (Mount Kisco, N.Y.)
BACKGROUND AND PURPOSE: In this review we describe the use of artificial intelligence in the field of echocardiography. Various aspects and terminologies used in artificial intelligence are explained in an easy-to-understand manner and supplemented w...

Assessment and validation of a novel fast fully automated artificial intelligence left ventricular ejection fraction quantification software.

Echocardiography (Mount Kisco, N.Y.)
BACKGROUND: Quantification of left ventricular ejection fraction (LVEF) by transthoracic echocardiography (TTE) is operator-dependent, time-consuming, and error-prone. LVivoEF by DIA is a new artificial intelligence (AI) software, which displays the ...

Applications of artificial intelligence and machine learning approaches in echocardiography.

Echocardiography (Mount Kisco, N.Y.)
Artificial intelligence and machine learning approaches have become increasingly applied in the field of echocardiography to streamline diagnostic and prognostic assessments, and to support treatment decisions. Artificial intelligence and machine lea...

Statistical and machine learning methodology for abdominal aortic aneurysm prediction from ultrasound screenings.

Echocardiography (Mount Kisco, N.Y.)
A method of analysis of a database of patients (n = 10 329) screened for an abdominal aortic aneurysm (AAA) is presented. Self-reported height, weight, age, gender, ethnicity, and parameters "Heart Problems," "Hypertension," "High Cholesterol," "Diab...

Automated, machine learning-based, 3D echocardiographic quantification of left ventricular mass.

Echocardiography (Mount Kisco, N.Y.)
BACKGROUND: Although 3D echocardiography (3DE) circumvents many limitations of 2D echocardiography by allowing direct measurements of left ventricular (LV) mass, it is seldom used in clinical practice due to time-consuming analysis. A recently develo...

Deep learning for predicting in-hospital mortality among heart disease patients based on echocardiography.

Echocardiography (Mount Kisco, N.Y.)
BACKGROUND: Heart disease (HD) is the leading cause of global death; there are several mortality prediction models of HD for identifying critically-ill patients and for guiding decision making. The existing models, however, cannot be used during init...

Automation, machine learning, and artificial intelligence in echocardiography: A brave new world.

Echocardiography (Mount Kisco, N.Y.)
Automation, machine learning, and artificial intelligence (AI) are changing the landscape of echocardiography providing complimentary tools to physicians to enhance patient care. Multiple vendor software programs have incorporated automation to impro...

From Acquisition to Prognosis: The Role of AI in Cardiac Magnetic Resonance Imaging Evaluation of Ischemic Cardiomyopathy.

Echocardiography (Mount Kisco, N.Y.)
Acute and chronic ischemic cardiomyopathy (ICM) still represents a leading cause of morbidity and mortality. Cardiac magnetic resonance (CMR) imaging plays a central role in the diagnosis and management of ICM, offering detailed visualization of card...