Deploying machine learning with messy, real world data in low- and middle-income countries: developing a global health use case

HIGHLIGHTS

• who: Amy Finnegan from the Johns Hopkins University, United States have published the paper: Deploying machine learning with messy, real world data in low- and middle-income countries: Developing a global health use case, in the Journal: (JOURNAL)
• what: The aim of this community case study is to describe the results of a machine_learning pilot at IntraHealth International to determine the amount of time, effort, and team composition that is necessary to incorporate machine_learning into the field programs. Dropbox offered the type of file and directory resources needed for versioning the data, a common access . . .
  

   

  

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