Developing a predictive model for plasmodium knowlesi-susceptible areas in Malaysia using geospatial data and artificial neural networks

Developing a predictive model for plasmodium knowlesi-susceptible areas in Malaysia using geospatial data and artificial neural networks

Plasmodium knowlesi is an emerging species for malaria in Malaysia, particularly in East Malaysia. This infection contributes to almost half of all malaria cases and deaths in Malaysia and poses a challenge in eradicating malaria. The aim of this study was to develop a predictive model for P. knowle...

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Bibliographic Details
Main Authors: Hod, Rozita, Mokhtar, Siti Aisah, Muharam, Farrah Melissa, Shamsudin, Ummi Kalthom, Hashim, Jamal Hisham
Format: Article
Language:en
Published: SAGE Publications 2021
Online Access:http://psasir.upm.edu.my/id/eprint/96673/1/ABSTRACT.pdf
http://psasir.upm.edu.my/id/eprint/96673/
https://journals.sagepub.com/doi/10.1177/10105395211048620?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%20%200pubmed
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http://psasir.upm.edu.my/id/eprint/96673/1/ABSTRACT.pdf
http://psasir.upm.edu.my/id/eprint/96673/
https://journals.sagepub.com/doi/10.1177/10105395211048620?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%20%200pubmed

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