{"id":45759,"date":"2023-11-20T05:32:46","date_gmt":"2023-11-20T11:32:46","guid":{"rendered":"https:\/\/stage.cancerimagingarchive.net\/tcia-citation\/luad-ct-survival-pub\/"},"modified":"2023-11-20T05:32:46","modified_gmt":"2023-11-20T11:32:46","slug":"luad-ct-survival-pub","status":"publish","type":"tcia_citation","link":"https:\/\/stage.cancerimagingarchive.net\/tcia-citation\/luad-ct-survival-pub\/","title":{"rendered":"LUAD-CT-SURVIVAL-PUB"},"template":"","class_list":["post-45759","tcia_citation","type-tcia_citation","status-publish"],"tcia_citation_type":"Publication Citation","tcia_citation_text":"<p><span>Paul, R., Hawkins, S., Balagurunathan, Y., Schabath, M., Gillies, R., Hall, L., &amp; Goldgof, D. (2016). <strong>Deep Feature Transfer Learning in Combination with Traditional Features Predicts Survival among Patients with Lung Adenocarcinoma<\/strong>. Tomography, 2(4), 388\u2013395. <a href=\"https:\/\/doi.org\/10.18383\/j.tom.2016.00211\">https:\/\/doi.org\/10.18383\/j.tom.2016.00211<\/a> <\/span><\/p>\n","tcia_citation_statement":"","tcia_citation_doi":"10.18383\/j.tom.2016.00211","_links":{"self":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/citations\/45759","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=45759"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}