Exploring the Impact of Batch Size on Deep Learning Artificial Intelligence Models for Malaria Detection-Reference-Cited by-同舟云学术

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Exploring the Impact of Batch Size on Deep Learning Artificial Intelligence Models for Malaria Detection

Published:2024-05-13 Issue: Volume: Page:
ISSN:2168-8184
Container-title:Cureus
language:en
Short-container-title:

Author:

Muralidhar Rohit,Demory Michelle L,Kesselman Marc M

Publisher

Springer Science and Business Media LLC

Reference25 articles.

1. World malaria report 2022. (2022). Accessed. April 29, 2024: https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2022.

2. World malaria report 2021. (2021). Accessed. April 29, 2024: https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2021.

3. Plasmodium genomics and genetics: new insights into malaria pathogenesis, drug resistance, epidemiology, and evolution;Su XZ;Clin Microbiol Rev,2019

4. Clinical review: severe malaria;Trampuz A;Crit Care,2003

5. Malaria;Garcia LS;Clin Lab Med,2010

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