{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T09:49:37Z","timestamp":1747216177201,"version":"3.40.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"print","value":"9781643684567"},{"type":"electronic","value":"9781643684574"}],"license":[{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,3,1]]},"abstract":"<jats:p>Hepatocellular carcinoma (HCC) is one of the most common cancers in the world which ranks fourth in cancer deaths. Primary pathological necrosis is an effective prognostic indicator for hepatocellular carcinoma. We propose a GCN-based approach that mimics the pathologist\u2019s perspective for global assessment of necrosis tissue distribution to analyze patient survival. Specifically, we introduced a graph convolutional neural network to construct a spatial map with necrotic tissue and tumor tissue as graph nodes, aiming to mine the contextual information between necrotic tissue in pathological sections. We used 1381 slides from 303 patients from the First Affiliated Hospital of Zhejiang University School to train the model and used TCGA-LIHC for external validation. The C-index of our method outperforms the baseline by about 4.45%, which proves that the information about the spatial distribution of necrosis learned by GCN is meaningful for guiding patient prognosis<\/jats:p>","DOI":"10.3233\/shti231328","type":"book-chapter","created":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T14:53:14Z","timestamp":1709304794000},"source":"Crossref","is-referenced-by-count":0,"title":["GCN-Based Risk Prediction for Necrosis Slide of Hepatocellular Carcinoma"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-7130-3372","authenticated-orcid":false,"given":"Boyang","family":"Deng","sequence":"first","affiliation":[{"name":"Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6791-8217","authenticated-orcid":false,"given":"Yu","family":"Tian","sequence":"additional","affiliation":[{"name":"Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7185-6944","authenticated-orcid":false,"given":"Qiancheng","family":"Ye","sequence":"additional","affiliation":[{"name":"Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3861-6978","authenticated-orcid":false,"given":"Zhenxing","family":"Chai","sequence":"additional","affiliation":[{"name":"Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5858-6353","authenticated-orcid":false,"given":"Tianshu","family":"Zhou","sequence":"additional","affiliation":[{"name":"Research Center for Healthcare Data Science, Zhejiang Laboratory, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0516-8008","authenticated-orcid":false,"given":"Qi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0143-3353","authenticated-orcid":false,"given":"Tingbo","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1064-637X","authenticated-orcid":false,"given":"Jingsong","family":"Li","sequence":"additional","affiliation":[{"name":"Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China"},{"name":"Research Center for Healthcare Data Science, Zhejiang Laboratory, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2023 \u2014 The Future Is Accessible"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI231328","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T14:53:16Z","timestamp":1709304796000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI231328"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,1]]},"ISBN":["9781643684567","9781643684574"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti231328","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2024,3,1]]}}}