COVID-19 Patient Recovery Prediction Using Efficient Logistic Regression Model

Shrawan Kumar Trivedi; Rajiv Kumar; Shubhamoy Dey; Amit Kumar Chaudhary; Justin Zuopeng Zhang

doi:10.1007/978-3-031-22018-0_13

COVID-19 Patient Recovery Prediction Using Efficient Logistic Regression Model

Shrawan Kumar Trivedi, Rajiv Kumar, Shubhamoy Dey, Amit Kumar Chaudhary, Justin Zuopeng Zhang

Management

Research output: Chapter or Contribution to Book › Literary contribution

Original language	English
Title of host publication	International Conference on Cyber Security, Privacy and Networking, ICSPN 2022
Editors	Nadia Nedjah, Gregorio Martínez Pérez, B.B. Gupta
Pages	134-149
Number of pages	16
DOIs	https://doi.org/10.1007/978-3-031-22018-0_13
State	Published - 2023
Event	International Conference on Cyber Security, Privacy and Networking, ICSPN 2022 - Virtual, Online Duration: Sep 9 2021 → Sep 11 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	599 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	International Conference on Cyber Security, Privacy and Networking, ICSPN 2022
City	Virtual, Online
Period	9/9/21 → 9/11/21

ASJC Scopus Subject Areas

Control and Systems Engineering
Signal Processing
Computer Networks and Communications

Keywords

COVID-19
Efficient logistic regression
Machine learning
Predicting patient recovery

Access to Document

10.1007/978-3-031-22018-0_13

Cite this

Trivedi, S. K., Kumar, R., Dey, S., Chaudhary, A. K., & Zhang, J. Z. (2023). COVID-19 Patient Recovery Prediction Using Efficient Logistic Regression Model. In N. Nedjah, G. Martínez Pérez, & B. B. Gupta (Eds.), International Conference on Cyber Security, Privacy and Networking, ICSPN 2022 (pp. 134-149). (Lecture Notes in Networks and Systems; Vol. 599 LNNS). https://doi.org/10.1007/978-3-031-22018-0_13

COVID-19 Patient Recovery Prediction Using Efficient Logistic Regression Model. / Trivedi, Shrawan Kumar; Kumar, Rajiv; Dey, Shubhamoy et al.
International Conference on Cyber Security, Privacy and Networking, ICSPN 2022. ed. / Nadia Nedjah; Gregorio Martínez Pérez; B.B. Gupta. 2023. p. 134-149 (Lecture Notes in Networks and Systems; Vol. 599 LNNS).

Research output: Chapter or Contribution to Book › Literary contribution

Trivedi, SK, Kumar, R, Dey, S, Chaudhary, AK & Zhang, JZ 2023, COVID-19 Patient Recovery Prediction Using Efficient Logistic Regression Model. in N Nedjah, G Martínez Pérez & BB Gupta (eds), International Conference on Cyber Security, Privacy and Networking, ICSPN 2022. Lecture Notes in Networks and Systems, vol. 599 LNNS, pp. 134-149, International Conference on Cyber Security, Privacy and Networking, ICSPN 2022, Virtual, Online, 9/9/21. https://doi.org/10.1007/978-3-031-22018-0_13

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title = "COVID-19 Patient Recovery Prediction Using Efficient Logistic Regression Model",

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author = "Trivedi, {Shrawan Kumar} and Rajiv Kumar and Shubhamoy Dey and Chaudhary, {Amit Kumar} and Zhang, {Justin Zuopeng}",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference on Cyber Security, Privacy and Networking, ICSPN 2022 ; Conference date: 09-09-2021 Through 11-09-2021",

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COVID-19 Patient Recovery Prediction Using Efficient Logistic Regression Model

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

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