AIMC Topic: Echocardiography
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Artificial intelligence in the diagnosis and detection of heart failure: the past, present, and future.
Reviews in cardiovascular medicine
Dec 22, 2021
Artificial Intelligence (AI) performs human intelligence-dependant tasks using tools such as Machine Learning, and its subtype Deep Learning. AI has incorporated itself in the field of cardiovascular medicine, and increasingly employed to revolutioni...
Towards automatic diagnosis of rheumatic heart disease on echocardiographic exams through video-based deep learning.
Journal of the American Medical Informatics Association : JAMIA
Aug 13, 2021
OBJECTIVE: Rheumatic heart disease (RHD) affects an estimated 39 million people worldwide and is the most common acquired heart disease in children and young adults. Echocardiograms are the gold standard for diagnosis of RHD, but there is a shortage ...
Utility of a Deep-Learning Algorithm to Guide Novices to Acquire Echocardiograms for Limited Diagnostic Use.
JAMA cardiology
Jun 1, 2021
IMPORTANCE: Artificial intelligence (AI) has been applied to analysis of medical imaging in recent years, but AI to guide the acquisition of ultrasonography images is a novel area of investigation. A novel deep-learning (DL) algorithm, trained on mor...
[Progress in cardiac imaging: from echocardiography to multimodality imaging].
Giornale italiano di cardiologia (2006)
Feb 1, 2021
In the last few decades, echocardiography has represented one of the technological fields with the fastest evolution and progress. As a non-invasive method at relative low cost, it is also suitable for the future to an increasingly integrated use in ...
Guiding ultrasound image capture with artificial intelligence.
Lancet (London, England)
Sep 12, 2020
Machine Learning Assessment of Left Ventricular Diastolic Function Based on Electrocardiographic Features.
Journal of the American College of Cardiology
Aug 25, 2020
BACKGROUND: Left ventricular (LV) diastolic dysfunction is recognized as playing a major role in the pathophysiology of heart failure; however, clinical tools for identifying diastolic dysfunction before echocardiography remain imprecise.
Classification of Aortic Stenosis Using ECG by Deep Learning and its Analysis Using Grad-CAM.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2020
This paper proposes an automatic method for classifying Aortic valvular stenosis (AS) using ECG (Electrocardiogram) images by the deep learning whose training ECG images are annotated by the diagnoses given by the medical doctor who observes the echo...
Artificial intelligence capable of detecting left ventricular hypertrophy: pushing the limits of the electrocardiogram?
Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
Mar 1, 2020
Comparing the performance of artificial intelligence and conventional diagnosis criteria for detecting left ventricular hypertrophy using electrocardiography.
Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
Mar 1, 2020
AIMS: Although left ventricular hypertrophy (LVH) has a high incidence and clinical importance, the conventional diagnosis criteria for detecting LVH using electrocardiography (ECG) has not been satisfied. We aimed to develop an artificial intelligen...
Real-time Detection of Aortic Valve in Echocardiography using Convolutional Neural Networks.
Current medical imaging
Jan 1, 2020
BACKGROUND: Valvular heart disease is a serious disease leading to mortality and increasing medical care cost. The aortic valve is the most common valve affected by this disease. Doctors rely on echocardiogram for diagnosing and evaluating valvular h...
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