Integrated Weight – CADEN Approach for post-COVID Cardiovascular  Symptom Detection in Deep Learning Optimization Techniques

D. Jeyabharathi , N. N. Krishna Veni , and E. Sucila

Integrated Weight – CADEN Approach for post-COVID Cardiovascular Symptom Detection in Deep Learning Optimization Techniques

Authors

D. Jeyabharathi , N. N. Krishna Veni , and E. Sucila

Keywords:

Cardiovascular Disease, post-COVID symptom, HMPV, Optimized Kernel Principal Component Analysis, Hybrid Hippo-Fish Optimization and Weighted Voting.

Abstract

The COVID-19 pandemic and human metapneumovirus (HMPV) have had a significant impact on global health.Recent findings describe the spectrum of adverse cardiovascular outcomes following COVID-19 infection. Early detection enables timely treatment, preventing future damage,

References

. Tamene E, Beyene A, Atsbeha H, Shimelis T. The diagnostic performance evaluation of Panbio and STANDARD Q coronavirus disease 2019 antigen tests against real-time polymerase chain reaction in southern Ethiopia. Scientific reports. 2024; 24;14(1):4556.

Downloads

Published

2024-05-08

How to Cite

D. Jeyabharathi , N. N. Krishna Veni , and E. Sucila. (2024). Integrated Weight – CADEN Approach for post-COVID Cardiovascular Symptom Detection in Deep Learning Optimization Techniques. Journal of Computational Analysis and Applications (JoCAAA), 33(05), 3624–3671. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/5026