{"id":42865,"date":"2023-11-20T02:56:54","date_gmt":"2023-11-20T08:56:54","guid":{"rendered":"https:\/\/stage.cancerimagingarchive.net\/tcia-citation\/hcc-tace-seg-pub\/"},"modified":"2023-11-20T02:56:54","modified_gmt":"2023-11-20T08:56:54","slug":"hcc-tace-seg-pub","status":"publish","type":"tcia_citation","link":"https:\/\/stage.cancerimagingarchive.net\/tcia-citation\/hcc-tace-seg-pub\/","title":{"rendered":"HCC-TACE-SEG-PUB"},"template":"","class_list":["post-42865","tcia_citation","type-tcia_citation","status-publish"],"tcia_citation_type":"Publication Citation","tcia_citation_text":"<p>Morshid, A., Elsayes, K. M., Khalaf, A. M., Elmohr, M. M., Yu, J., Kaseb, A. O., Hassan, M., Mahvash, A., Wang, Z., Hazle, J. D., &amp; Fuentes, D. (2019). <strong>A Machine Learning Model to Predict Hepatocellular Carcinoma Response to Transcatheter Arterial Chemoembolization.<\/strong> Radiology: Artificial Intelligence, 1(5), e180021. <a href=\"https:\/\/doi.org\/10.1148\/ryai.2019180021\">https:\/\/doi.org\/10.1148\/ryai.2019180021<\/a>\u00a0<\/p>\n","tcia_citation_statement":"","tcia_citation_doi":"10.1148\/ryai.2019180021","_links":{"self":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/citations\/42865","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=42865"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}