AIMC Topic: Heart Diseases
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Feasibility of a 5G-Based Robot-Assisted Remote Ultrasound System for Cardiopulmonary Assessment of Patients With Coronavirus Disease 2019.
Chest
Jul 9, 2020
BACKGROUND: Traditional methods for cardiopulmonary assessment of patients with coronavirus disease 2019 (COVID-19) pose risks to both patients and examiners. This necessitates a remote examination of such patients without sacrificing information qua...
Deep learning using electrocardiographs.
The Lancet. Digital health
Jun 23, 2020
Automatic multilabel electrocardiogram diagnosis of heart rhythm or conduction abnormalities with deep learning: a cohort study.
The Lancet. Digital health
Jun 4, 2020
BACKGROUND: Market-applicable concurrent electrocardiogram (ECG) diagnosis for multiple heart abnormalities that covers a wide range of arrhythmias, with better-than-human accuracy, has not yet been developed. We therefore aimed to engineer a deep le...
Automatic Triage of 12-Lead ECGs Using Deep Convolutional Neural Networks.
Journal of the American Heart Association
May 14, 2020
BACKGROUND The correct interpretation of the ECG is pivotal for the accurate diagnosis of many cardiac abnormalities, and conventional computerized interpretation has not been able to reach physician-level accuracy in detecting (acute) cardiac abnorm...
Application of artificial intelligence in cardiac CT: From basics to clinical practice.
European journal of radiology
Apr 8, 2020
Research into the possibilities of AI in cardiac CT has been growing rapidly in the last decade. With the rise of publicly available databases and AI algorithms, many researchers and clinicians have started investigations into the use of AI in the cl...
Video-based AI for beat-to-beat assessment of cardiac function.
Nature
Mar 25, 2020
Accurate assessment of cardiac function is crucial for the diagnosis of cardiovascular disease, screening for cardiotoxicity and decisions regarding the clinical management of patients with a critical illness. However, human assessment of cardiac fun...
Value of a Machine Learning Approach for Predicting Clinical Outcomes in Young Patients With Hypertension.
Hypertension (Dallas, Tex. : 1979)
Mar 16, 2020
Risk stratification of young patients with hypertension remains challenging. Generally, machine learning (ML) is considered a promising alternative to traditional methods for clinical predictions because it is capable of processing large amounts of c...
Automated segmentation of the left ventricle from MR cine imaging based on deep learning architecture.
Biomedical physics & engineering express
Feb 18, 2020
BACKGROUND: Magnetic resonance cine imaging is the accepted standard for cardiac functional assessment. Left ventricular (LV) segmentation plays a key role in volumetric functional quantification of the heart. Conventional manual analysis is time-con...
Towards Domain Invariant Heart Sound Abnormality Detection Using Learnable Filterbanks.
IEEE journal of biomedical and health informatics
Jan 31, 2020
OBJECTIVE: Cardiac auscultation is the most practiced non-invasive and cost-effective procedure for the early diagnosis of heart diseases. While machine learning based systems can aid in automatically screening patients, the robustness of these syste...
Comprehensive electrocardiographic diagnosis based on deep learning.
Artificial intelligence in medicine
Jan 20, 2020
Cardiovascular disease (CVD) is the leading cause of death worldwide, and coronary artery disease (CAD) is a major contributor. Early-stage CAD can progress if undiagnosed and left untreated, leading to myocardial infarction (MI) that may induce irre...
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