Effective Prediction Analysis for Cardiovascular Using Various Machine Learning Algorithms-Reference-Cited by-同舟云学术

Effective Prediction Analysis for Cardiovascular Using Various Machine Learning Algorithms

Published:2023 Issue: Volume: Page:641-650
ISSN:2367-3370
Container-title:Lecture Notes in Networks and Systems
language:
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Author:

Shanmuga Sundari M.^ORCID,Dyva Sugnana Rao M.,Kumar Ch Anil

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-8563-8_62

Reference21 articles.

1. Rubini PE, Subasini CA, Vanitha Katharine A, Kumaresan V, Gowdham Kumar S, Nithya TM (2021) A cardiovascular disease prediction using machine learning algorithms. Ann Romanian Soc Cell Biol 904–912

2. El-Ganainy NO, Balasingham I, Halvorsen PS, Rosseland LA (2020) A new real time clinical decision support system using machine learning for critical care units. IEEE Access 8:185676–185687

3. Wu J, Guo P, Cheng Y, Zhu H, Wang XB, Shao X (2020) Ensemble generalized multiclass support-vector-machine-based health evaluation of complex degradation systems. IEEE/ASME Trans Mechatron 25(5):2230–2240

4. Ksantini R, Ziou D, Colin B, Dubeau F (2007) Weighted pseudometric discriminatory power improvement using a bayesian logistic regression model based on a variational method. IEEE Trans Pattern Anal Mach Intell 30(2):253–266

5. Costilla-Enriquez N, Weng Y, Zhang B (2020) Combining Newton-Raphson and stochastic gradient descent for power flow analysis. IEEE Trans Power Syst 36(1):514–517

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