{
  "abstract": "Nina Linder and colleagues examine how artificial intelligence could be applied to diagnostic methods that rely on highly trained experts, such as cytological screening for cervical cancer, enabling implementation even in resource limited settings",
  "authors": [
    {
      "affiliations": [
        "Global Health and Migration Unit, Department of Women’s and Children’s Health, Uppsala university, Uppsala, Sweden",
        "Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland"
      ],
      "name": "Nina Linder"
    },
    {
      "affiliations": [
        "Muhimbili University of Health and Allied Sciences (MUHAS), Dar es Salaam, Tanzania"
      ],
      "name": "Dinnah Nyirenda"
    },
    {
      "affiliations": [
        "Global Health and Migration Unit, Department of Women’s and Children’s Health, Uppsala university, Uppsala, Sweden",
        "Department of Infectious Diseases, Uppsala University Hospital, Uppsala, Sweden"
      ],
      "name": "Andreas Mårtensson"
    },
    {
      "affiliations": [
        "Kinondo Kwetu Hospital, Kwale County, Kenya"
      ],
      "name": "Harrison Kaingu"
    },
    {
      "affiliations": [
        "Muhimbili University of Health and Allied Sciences (MUHAS), Dar es Salaam, Tanzania",
        "Global Health and Migration Unit, Department of Women’s and Children’s Health, Uppsala university, Uppsala, Sweden"
      ],
      "name": "Billy Ngasala"
    },
    {
      "affiliations": [
        "Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden",
        "Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland"
      ],
      "name": "Johan Lundin"
    }
  ],
  "title": "AI supported diagnostic innovations for impact in global women’s health",
  "uid": "6e827af8-a83e-51d4-bb95-297b331e8773"
}