Toward co-design of an AI solution for detection of diarrheal pathogens in drinking water within resource-constrained contexts.

Autor: Hall-Clifford R; Departments of Sociology and Global Health, Center for the Study of Human Health, Emory University, Decatur, GA, United States of America., Arzu A; Center for the Study of Human Health, Emory University, Decatur, GA, United States of America., Contreras S; Department of Computer Sciences, Universidad del Valle de Guatemala, Guatemala City, Guatemala., Croissert Muguercia MG; Department of Biochemistry, Universidad del Valle de Guatemala, Guatemala City, Guatemala., de Leon Figueroa DX; Department of Computer Sciences, Universidad del Valle de Guatemala, Guatemala City, Guatemala., Ochoa Elias MV; Department of Biochemistry, Universidad del Valle de Guatemala, Guatemala City, Guatemala., Soto Fernández AY; Center for Biotechnology Studies, Universidad del Valle de Guatemala, Guatemala City, Guatemala., Tariq A; Machine Intelligence in Medicine and Imaging (MI-2) Lab, Mayo Clinic, Phoenix, Arizona, United States of America., Banerjee I; Department of Radiology, Mayo Clinic, Phoenix, Arizona, United States of America.; School of Computing and Augmented Intelligence, Arizona State University, Tempe, Arizona, United States of America., Pennington P; Center for Biotechnology Studies, Universidad del Valle de Guatemala, Guatemala City, Guatemala.

Publikováno v: PLOS global public health [PLOS Glob Public Health] 2022 Aug 16; Vol. 2 (8), pp. e0000918. Date of Electronic Publication: 2022 Aug 16 (Print Publication: 2022).