Field evaluation of the diagnostic performance of EasyScan GO: a digital malaria microscopy device based on machine-learning

MLA

Debashish Das, et al. “Field Evaluation of the Diagnostic Performance of EasyScan GO: A Digital Malaria Microscopy Device Based on Machine-Learning.” Malaria Journal, vol. 21, no. 1, Apr. 2022, pp. 1–12. EBSCOhost, https://doi.org/10.1186/s12936-022-04146-1.

APA

Debashish Das, Ranitha Vongpromek, Thanawat Assawariyathipat, Ketsanee Srinamon, Kalynn Kennon, Kasia Stepniewska, Aniruddha Ghose, Abdullah Abu Sayeed, M. Abul Faiz, Rebeca Linhares Abreu Netto, Andre Siqueira, Serge R. Yerbanga, Jean Bosco Ouédraogo, James J. Callery, Thomas J. Peto, Rupam Tripura, Felix Koukouikila-Koussounda, Francine Ntoumi, John Michael Ong’echa, … Mehul Dhorda. (2022). Field evaluation of the diagnostic performance of EasyScan GO: a digital malaria microscopy device based on machine-learning. Malaria Journal, 21(1), 1–12. https://doi.org/10.1186/s12936-022-04146-1

Chicago

Debashish Das, Ranitha Vongpromek, Thanawat Assawariyathipat, Ketsanee Srinamon, Kalynn Kennon, Kasia Stepniewska, Aniruddha Ghose, et al. 2022. “Field Evaluation of the Diagnostic Performance of EasyScan GO: A Digital Malaria Microscopy Device Based on Machine-Learning.” Malaria Journal 21 (1): 1–12. doi:10.1186/s12936-022-04146-1.