Additional file 3 of Field evaluation of the diagnostic performance of EasyScan GO: a digital malaria microscopy device based on machine-learning

Authors :: Das, Debashish
Vongpromek, Ranitha
Assawariyathipat, Thanawat
Srinamon, Ketsanee
Kennon, Kalynn
Stepniewska, Kasia
Ghose, Aniruddha
Sayeed, Abdullah Abu
Faiz, M. Abul
Netto, Rebeca Linhares Abreu
Siqueira, Andre
Yerbanga, Serge R.
Ouédraogo, Jean Bosco
Callery, James J.
Peto, Thomas J.
Tripura, Rupam
Koukouikila-Koussounda, Felix
Ntoumi, Francine
Ong’echa, John Michael
Ogutu, Bernhards
Ghimire, Prakash
Marfurt, Jutta
Ley, Benedikt
Seck, Amadou
Ndiaye, Magatte
Moodley, Bhavani
Sun, Lisa Ming
Archasuksan, Laypaw
Proux, Stephane
Nsobya, Sam L.
Rosenthal, Philip J.
Horning, Matthew P.
McGuire, Shawn K.
Mehanian, Courosh
Burkot, Stephen
Delahunt, Charles B.
Bachman, Christine
Price, Ric N.
Dondorp, Arjen M.
Chappuis, François
Guérin, Philippe J.
Dhorda, Mehul
Publication Year :: 2022
Publisher :: figshare, 2022.
Abstract: Additional file 3. EasyScan Go.

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