{"id":41409,"date":"2023-11-20T01:00:10","date_gmt":"2023-11-20T07:00:10","guid":{"rendered":"https:\/\/stage.cancerimagingarchive.net\/tcia-citation\/bone-marrow-cytomorphology_mll_helmholtz_fraunhofer-pub\/"},"modified":"2023-11-20T01:00:10","modified_gmt":"2023-11-20T07:00:10","slug":"bone-marrow-cytomorphology_mll_helmholtz_fraunhofer-pub","status":"publish","type":"tcia_citation","link":"https:\/\/stage.cancerimagingarchive.net\/tcia-citation\/bone-marrow-cytomorphology_mll_helmholtz_fraunhofer-pub\/","title":{"rendered":"BONE-MARROW-CYTOMORPHOLOGY_MLL_HELMHOLTZ_FRAUNHOFER-PUB"},"template":"","class_list":["post-41409","tcia_citation","type-tcia_citation","status-publish"],"tcia_citation_type":"Publication Citation","tcia_citation_text":"<p><span>Matek, C., Krappe, S., M\u00fcnzenmayer, C., Haferlach, T., and Marr, C. (2021). <strong>Highly accurate differentiation of bone marrow cell morphologies using deep neural networks on a large image dataset.<\/strong> <a href=\"https:\/\/doi.org\/10.1182\/blood.2020010568\" title=\"Persistent link using digital object identifier\">https:\/\/doi.org\/10.1182\/blood.2020010568<\/a><\/span><\/p>\n","tcia_citation_statement":"","tcia_citation_doi":"10.1182\/blood.2020010568","_links":{"self":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/citations\/41409","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/citations"}],"about":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/wp\/v2\/types\/tcia_citation"}],"wp:attachment":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/wp\/v2\/media?parent=41409"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}