Detection of cardiac amyloidosis on electrocardiogram images using machine learning and deep learning techniques

Author:

Gnanadurai Gladys Jebakumari1,Raaza Arun1,Velayutham Rajendran1,Palani Sathish Kumar1,Bramwell Ebenezer Abishek1

Affiliation:

1. Department of Electronics and Communication Engineering Vels Institute of Science, Technology & Advanced Studies (VISTAS) Chennai India

Publisher

Wiley

Subject

Artificial Intelligence,Computational Mathematics

Reference38 articles.

1. Heart failure with preserved ejection fraction—a concise review;Adamczak DM;Curr Cardiol Rep,2020

2. Machine learning enables prediction of cardiac amyloidosis by routine laboratory parameters: a proof‐of‐concept study;Agibetov A;J Clin Med,2020

3. Applications of artificial intelligence and deep learning in molecular imaging and radiotherapy;Arabi H;Eur J Hybrid Imaging,2020

4. Regression of cardiac amyloidosis following stem cell transplantation: a comparison between echocardiography and cardiac magnetic resonance imaging in long‐term survivors;Fitzgerald BT;IJC Heart Vasc,2017

5. Identification of the best anthropometric predictors of serum high‐ and low‐density lipoproteins using machine learning;Lee BJ;IEEE J Biomed Health Inform,2015

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