학술논문
Field evaluation of the diagnostic performance of EasyScan GO: a digital malaria microscopy device based on machine-learning
Document Type
Article
Author
Das, D.; Vongpromek, R.; Assawariyathipat, T.; Kennon, K.; Stepniewska, K.; Guérin, P.J.; Dhorda, M.; Callery, J.J.; Peto, T.J.; Tripura, R.; Price, R.N.; Dondorp, A.M.; Srinamon, K.; Ghose, A.; Sayeed, A.A.; Faiz, M.A.; Netto, R.L.A.; Siqueira, A.; Yerbanga, S.R.; Ouédraogo, J.B.; Koukouikila-Koussounda, F.; Ntoumi, F.; Ong’echa, J.M.; Ogutu, B.; Ghimire, P.; Marfurt, J.; Ley, B.; Seck, A.; Ndiaye, M.; Moodley, B.; Sun, L.M.; Archasuksan, L.; Proux, S.; Nsobya, S.L.; Rosenthal, P.J.; Horning, M.P.; McGuire, S.K.; Mehanian, C.; Burkot, S.; Delahunt, C.B.; Bachman, C.; Chappuis, F.
Source
In: Malaria Journal . (Malaria Journal, December 2022, 21(1))
Subject
Language
English
ISSN
14752875