Towards applying internet of things and machine learning for the risk prediction of COVID-19 in pandemic situation using Naive Bayes classifier for improving accuracy-Reference-Cited by-同舟云学术

Towards applying internet of things and machine learning for the risk prediction of COVID-19 in pandemic situation using Naive Bayes classifier for improving accuracy

Published:2022 Issue: Volume:62 Page:4795-4799
ISSN:2214-7853
Container-title:Materials Today: Proceedings
language:en
Short-container-title:Materials Today: Proceedings

Author:

Deepa N.,Sathya Priya J.,Devi T.

Publisher

Elsevier BV

Subject

General Medicine

Reference13 articles.

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3. Absalom E. Ezugwu, Ibrahim Abaker Targio Hashem, Olaide N. Oyelade, Mubarak Almutari, Mohammed A. Al-Garadi, Idris Nasir Abdullahi, Olumuyiwa Otegbeye , Amit K. Shukla, and Haruna Chiroma, A novel smart city-based framework on perspectives for application of machine learning in combating COVID-19, Cloud Analytic Based Applications for Bioinformatics, Vol. 2021.

4. M. Golec, R. Ozturac, Z. Pooranian, S. S. Gill, R. Buyya, iFaaSBus: A Security and Privacy based Lightweight Framework for Serverless Computing using IoT and Machine Learning, in: IEEE Transactions on Industrial Informatics.

5. R. Mukherjee, A. Kundu, I. Mukherjee, et al., IoT-cloud based healthcare model for COVID-19 detection: an enhanced k-Nearest Neighbour classifier based approach. Computing (2021).

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