A Novel Hyper-Spectral Model to Optimize the Prediction Rate for Heart Disease in Modern Healthcare Networks-Reference-Cited by-同舟云学术

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A Novel Hyper-Spectral Model to Optimize the Prediction Rate for Heart Disease in Modern Healthcare Networks

Published:2023-12-19 Issue: Volume: Page:
ISSN:
Container-title:RAiSE-2023
language:
Short-container-title:

Author:

Abinaya K.¹,Palaniappan Damodharan²,Vedaraj M.³

Affiliation:

1. Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Sathyabama College Road, Semmancheri, Chennai 600119, India

2. Department of Computer Engineering, Marwadi University, Rajkot 360003, India

3. Department of Computer Science and Engineering, R.M.D. Engineering College, Kavaraipettai, Gummidipoondi 601206, India

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/59/1/59081/pdf

Reference20 articles.

1. Lion based butterfly optimization with improved YOLO-v4 for heart disease prediction using IoMT;Alamelu;Inf. Technol. Control.,2022

2. A multi-variate heart disease optimization and recognition framework;Balaha;Neural Comput. Appl.,2022

3. Investigations on brain tumor classification using hybrid machine learning algorithms;Rinesh;J. Healthc. Eng.,2022

4. Yaqoob, M.M., Nazir, M., Khan, M.A., Qureshi, S., and Al-Rasheed, A. (2023). Hybrid classifier-based federated learning in health service providers for cardiovascular disease prediction. Appl. Sci., 13.

5. Qureshi, M., and Warke, N. (2022, January 14). Application of Machine Learning for Heart Disease Prediction. Proceedings of the 2nd International Conference on Artificial Intelligence: Advances and Applications (ICAIAA 2021), Singapore.

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