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"Deploying machine learning with messy, real world data in low- and ..."

Amy Finnegan et al. (2022)

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DOI: 10.3389/FDATA.2022.553673

access: open

type: Journal Article

metadata version: 2023-03-08

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  - https://dblp.org/rec/journals/fdata/FinneganPKWMEMSV22
Amy Finnegan, David D. Potenziani, Caroline Karutu, Irene Wanyana, Nicholas Matsiko, Cyrus Elahi, Nobert Mijumbi, Richard Stanley, Wayan Vota:
Deploying machine learning with messy, real world data in low- and middle-income countries: Developing a global health use case. Frontiers Big Data 5 (2022)

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