An RNN-Bi LSTM Based Multi Decision GAN Approach for the Recognition of Cardiovascular Disease (CVD) From Heart Beat Sound: A Feature Optimization Process-Reference-Cited by-同舟云学术

An RNN-Bi LSTM Based Multi Decision GAN Approach for the Recognition of Cardiovascular Disease (CVD) From Heart Beat Sound: A Feature Optimization Process

Published:2024 Issue: Volume:12 Page:65482-65502
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Vinay N. A.¹^ORCID,Vidyasagar K. N.²^ORCID,Rohith S.³^ORCID,Pruthviraja Dayananda⁴^ORCID,Supreeth S.⁵^ORCID,Bharathi S. H.²^ORCID

Affiliation:

1. Department of Electronics and Communication Engineering, Dayanand Sagar College of Engineering, Bengaluru, India

2. School of Electronics and Communication Engineering, REVA University, Bengaluru, India

3. Department of Electronics and Communication Engineering, Nagarjuna College of Engineering and Technology, Bengaluru, India

4. Department of Information Technology, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India

5. School of Computer Science and Engineering, REVA University, Bengaluru, India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10521503.pdf?arnumber=10521503

Reference47 articles.

1. Toward Automated Feature Extraction for Deep Learning Classification of Electrocardiogram Signals

2. A Novel Rapid Assessment of Mental Stress by Using PPG Signals Based on Deep Learning

3. HeartNet: Self Multihead Attention Mechanism via Convolutional Network With Adversarial Data Synthesis for ECG-Based Arrhythmia Classification

4. An Evolutionary-Neural Mechanism for Arrhythmia Classification With Optimum Features Using Single-Lead Electrocardiogram

5. Heartbeat Classification by Random Forest With a Novel Context Feature: A Segment Label

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