Automating Malaria Diagnosis with XAI: Using Deep-Learning Technologies for More Accurate, Efficient, and Transparent Results-Reference-Cited by-同舟云学术

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Automating Malaria Diagnosis with XAI: Using Deep-Learning Technologies for More Accurate, Efficient, and Transparent Results

Published:2023 Issue: Volume: Page:297-308
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Mridha Krishan^ORCID,Tola Fitsum Getachew^ORCID,Sarkar Shakil,Arefin Nazmul,Ghimire Sandesh,Aran Anmol,Pandey Aashish Prashad

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-36402-0_27

Reference28 articles.

1. Fact Sheet about Malaria: https://www.who.int/news-room/fact-sheets/detail/malaria (2019). Accessed 29 Dec 2019

2. Fact Sheet about MALARIA: https://www.who.int/news-room/fact-sheets/detail/malaria (2020). Accessed on 12 Apr 2020

3. Wongsrichanalai, C., Barcus, M.J., Muth, S., Sutamihardja, A., Wernsdorfer, W.H.: A review of malaria diagnostic tools: Microscopy and rapid diagnostic test (rdt). Am. J. Trop. Med. Hyg. 77(Suppl. 6), 119–127 (2007)

4. WHO: New Perspectives: Malaria Diagnosis. Report of a Joint WHO/USAID Informal Consultation (Archived). https://www.who.int/malaria/publications/atoz/who_cds_rbm_2000_14/en/ (2020). Accessed on 9 Apr 2020

5. Obeagu, E.I., Chijioke, U.O., Ekelozie, I.S.: Malaria rapid diagnostic test (RDTs). Ann. Clin. Lab. Res. 6, 275 (2018)

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