Simple Non-Invasive Coronary Artery Disease Detection Using Machine Learning-Reference-Cited by-同舟云学术

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Simple Non-Invasive Coronary Artery Disease Detection Using Machine Learning

Published:2024-02-21 Issue: Volume:16 Page:1-6
ISSN:
Container-title:2024 4th International Conference on Innovative Practices in Technology and Management (ICIPTM)
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Author:

Kalpana S.¹,Srither S. R.²,Dhineshbabu N. R.³,Nikitha G.⁴

Affiliation:

1. Velagapudi Ramakrishna Siddhartha Engineering College,Department of Electronics and Instrumentation Engineering,Vijayawada,Andhra Pradesh,India,520007

2. Koneru Lakshmaiah Education Foundation,Center for Flexible Electronics,Department of Electronics and Communication Engineering,Andhra Pradesh,India,522302

3. T. John Institute of Technology,Department of Electronics and Communication Engineering,Bangalore,India,560018

4. Velagapudi Ramakrishna Siddhartha Engineering College,Department of Electronics and Instrumentation Engineering,Vijayawada,Andhra Pradesh,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10562381/10563197/10563565.pdf?arnumber=10563565

Reference15 articles.

1. Initial evaluation of a convolutional neural network used for noninvasive assessment of coronary artery disease severity from coronary computed tomography angiography data

2. Detection of abnormal left ventricular geometry in patients without cardiovascular disease through machine learning: An ECG‐based approach

3. A machine learning algorithm to predict a culprit lesion after out of hospital cardiac arrest

4. Deep learning in ECG diagnosis: A review

5. Risks and Complications of Coronary Angiography: A Comprehensive Review

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