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Using artificial intelligence on dermatology conditions in Uganda: A case for diversity in training data sets for machine learning

Louis Henry Kamulegeya, Mark Okello, John Mark Bwanika, Davis Musinguzi, William Lubega, Davis Rusoke, Faith Nassiwa, Alexander Börve
doi: https://doi.org/10.1101/826057

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doi 
https://doi.org/10.1101/826057
History 
  • October 31, 2019.
Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.

Author Information

  1. Louis Henry Kamulegeya1,*,
  2. Mark Okello1,,
  3. John Mark Bwanika1,&,
  4. Davis Musinguzi1,&,
  5. William Lubega1,&,
  6. Davis Rusoke1,&,
  7. Faith Nassiwa1,& and
  8. Alexander Börve2,
  1. 1The Medical Concierge Group, Kampala- Uganda
  2. 2Departments of Orthopaedics, Sahlgrenska University Hospital, Institute of Clinical Sciences at the Sahlgrenska Academy, University of Gothenburg, Sweden
  1. ↵*Corresponding Author louiskamu{at}gmail.com (LHK)

  1. ↵ These authors contributed equally to this work.

  2. ↵& These authors also contributed equally to this work.

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Posted October 31, 2019.
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Using artificial intelligence on dermatology conditions in Uganda: A case for diversity in training data sets for machine learning
Louis Henry Kamulegeya, Mark Okello, John Mark Bwanika, Davis Musinguzi, William Lubega, Davis Rusoke, Faith Nassiwa, Alexander Börve
bioRxiv 826057; doi: https://doi.org/10.1101/826057
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