Point-of-Care Digital Cytology With Artificial Intelligence for Cervical Cancer Screening in a Resource-Limited Setting.

Journal: JAMA network open
PMID: 33729503

Abstract

IMPORTANCE: Cervical cancer is highly preventable but remains a common and deadly cancer in areas without screening programs. The creation of a diagnostic system to digitize Papanicolaou test samples and analyze them using a cloud-based deep learning system (DLS) may provide needed cervical cancer screening to resource-limited areas.

Authors

  • Oscar Holmström
    Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.
  • Nina Linder
    Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
  • Harrison Kaingu
    Kinondo Kwetu Health Services Clinic, Kinondo, Kenya.
  • Ngali Mbuuko
    Kinondo Kwetu Health Services Clinic, Kinondo, Kenya.
  • Jumaa Mbete
    Kinondo Kwetu Health Services Clinic, Kinondo, Kenya.
  • Felix Kinyua
    Kinondo Kwetu Health Services Clinic, Kinondo, Kenya.
  • Sara Törnquist
    Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.
  • Martin Muinde
    Kinondo Kwetu Health Services Clinic, Kinondo, Kenya.
  • Leena Krogerus
    Helsinki University Central Hospital Laboratory (HUSLAB), HUS Diagnostic Center, Helsinki and Uusimaa Hospital District, Helsinki, Finland.
  • Mikael Lundin
    Institute for Molecular Medicine Finland, HILIFE, University of Helsinki, Helsinki, Finland.
  • Vinod Diwan
    Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.
  • Johan Lundin
    Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.

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