Feature Selection Approach to Improve Malaria Prediction Model’s Performance for High- and Low-Endemic Areas of Tanzania-Reference-Cited by-同舟云学术

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Feature Selection Approach to Improve Malaria Prediction Model’s Performance for High- and Low-Endemic Areas of Tanzania

Published:2024 Issue: Volume: Page:53-69
ISSN:2196-8705
Container-title:Progress in IS
language:en
Short-container-title:

Author:

Mariki Martina^ORCID,Mduma Neema^ORCID,Mkoba Elizabeth^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-56576-2_6

Reference38 articles.

1. WHO. (2020). World malaria report 2020. World Health Organization. Retrieved May 29, 2021, from https://www.who.int/publications/i/item/9789240015791

2. WHO. (2019). World malaria report 2019. World Health Organization. Retrieved May 29, 2021, from https://www.who.int/publications/i/item/9789241565721

3. Chacky, F., et al. (2018, December). Nationwide school malaria parasitaemia survey in public primary schools, the United Republic of Tanzania. Malaria Journal, 17(1), 1–16. https://doi.org/10.1186/S12936-018-2601-1

4. Michael, D., & Mkunde, S. P. (2017, April). The malaria testing and treatment landscape in mainland Tanzania, 2016. Malaria Journal, 16(1), 1–15. https://doi.org/10.1186/S12936-017-1819-7

5. WHO. (2019). WHO | Guidelines for the treatment of malaria (3rd ed.). World Health Organization.

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