{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T16:03:18Z","timestamp":1778256198749,"version":"3.51.4"},"reference-count":64,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U22B2036"],"award-info":[{"award-number":["U22B2036"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U20B2065"],"award-info":[{"award-number":["U20B2065"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Project of Humanities and Social Sciences","award":["18YJC870001"],"award-info":[{"award-number":["18YJC870001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Biomed. Eng."],"published-print":{"date-parts":[[2023,12]]},"DOI":"10.1109\/tbme.2023.3280987","type":"journal-article","created":{"date-parts":[[2023,6,14]],"date-time":"2023-06-14T17:20:43Z","timestamp":1686763243000},"page":"3277-3287","source":"Crossref","is-referenced-by-count":15,"title":["Learning to Summarize Chinese Radiology Findings With a Pre-Trained Encoder"],"prefix":"10.1109","volume":"70","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8584-6376","authenticated-orcid":false,"given":"Zuowei","family":"Jiang","sequence":"first","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1406-107X","authenticated-orcid":false,"given":"Xiaoyan","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5316-7689","authenticated-orcid":false,"given":"Libin","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Cybersecurity, Northwestern Polytechnical University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6636-5702","authenticated-orcid":false,"given":"Dehong","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Cybersecurity, Northwestern Polytechnical University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8520-2087","authenticated-orcid":false,"given":"Wei","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Radiology, The Second Xiangya Hospital, Central South University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5545-7217","authenticated-orcid":false,"given":"Junwei","family":"Han","sequence":"additional","affiliation":[{"name":"School of Automation, Northwestern Polytechnical University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7851-6782","authenticated-orcid":false,"given":"Jun","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7934-5698","authenticated-orcid":false,"given":"Dinggang","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, ShanghaiTech University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8132-9048","authenticated-orcid":false,"given":"Tianming","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The University of Georgia, Athens, GA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"issue":"2","key":"ref1","first-page":"140","article-title":"The radiological report: What is useful for the referring physician","volume":"39","author":"Lafortune","year":"1988","journal-title":"Can. Assoc. Radiologists J.  J. lAssoc. Canadienne des Radiologistes"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-022-00712-w"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/d15-1044"},{"key":"ref4","first-page":"93","article-title":"Abstractive text summarization using sequence-to-sequence RNNs and beyond","volume-title":"Proc. Conf. North Amer. Chapter Assoc. Comput. Linguistics: Hum. Lang. Technol.","author":"Chopra"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1613\/jair.1523"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-017-1042-4"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00030"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-018-0595-9"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-019-0769-0"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1409.3215"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2829199"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2022.3207688"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.105964"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.116819"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113679"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.12.011"},{"issue":"1","key":"ref17","first-page":"5485","article-title":"Exploring the limits of transfer learning with a unified text-to-text transformer","volume":"21","author":"Raffel","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"ref18","first-page":"1","article-title":"A deep reinforced model for abstractive summarization","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Paulus"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P16-1154"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/p17-1099"},{"key":"ref21","article-title":"Unsupervised neural multi-document abstractive summarization","author":"Chu","year":"2018"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1101"},{"key":"ref23","article-title":"Continual BERT: Continual learning for adaptive extractive summarization of COVID-19 literature","author":"Park","year":"2020"},{"key":"ref24","article-title":"Automatic text summarization of COVID-19 medical research articles using BERT and GPT-2","author":"Kieuvongngam","year":"2020"},{"key":"ref25","first-page":"8739","article-title":"Improving language understanding by generative pre-training","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Radford","year":"2019"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1754\/1\/012213"},{"issue":"8","key":"ref27","article-title":"Language models are unsupervised multitask learners","volume":"1","author":"Radford","year":"2019","journal-title":"OpenAI blog"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.3390\/info9090217"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3407911"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1049\/cit2.12117"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3132724"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TAI.2022.3207982"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-03190-3"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102470"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2011.03.008"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2020.101878"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.101985"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.imu.2021.100557"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-017-0030-2"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.441"},{"key":"ref41","article-title":"Towards clinical encounter summarization: Learning to compose discharge summaries from prior notes","author":"Shing","year":"2021"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/tbme.2013.2283970"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/tbme.2004.840497"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/tbme.2018.2859322"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/tbme.2016.2553960"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3159980"},{"key":"ref47","article-title":"XLNet: Generalized autoregressive pretraining for language understanding","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Yang"},{"key":"ref48","first-page":"4171","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","volume-title":"Proc. NAACL-HLT","author":"Devlin"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btz682"},{"key":"ref50","article-title":"Conceptualized representation learning for Chinese biomedical text mining","author":"Zhang","year":"2020"},{"key":"ref51","first-page":"13063","article-title":"Unified language model pre-training for natural language understanding and generation","volume-title":"Proc. 33rd Int. Conf. Neural Inf. Process. Syst.","author":"Dong"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00417"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/s10590-009-9059-4"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00105"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1002\/jae.2939"},{"key":"ref56","first-page":"74","article-title":"Rouge: A package for automatic evaluation of summaries","volume-title":"Text Summarization Branches Out","author":"Lin","year":"2004"},{"key":"ref57","first-page":"3","article-title":"Machine translation and the evaluation of its quality","volume-title":"Proc. 22nd Int. Conf. Text, Speech, Dialogue","author":"Mauec","year":"2019"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/s10791-011-9172-x"},{"key":"ref59","article-title":"Fine-tune BERT for extractive summarization","author":"Liu","year":"2019"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1387"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.newsum-1.3"},{"key":"ref62","article-title":"Roberta: A robustly optimized BERT pretraining approach","author":"Liu","year":"2019"},{"key":"ref63","article-title":"Nezha: Neural contextualized representation for chinese language understanding","author":"Wei","year":"2019"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-021-01614-0"}],"container-title":["IEEE Transactions on Biomedical Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10\/10325330\/10152477.pdf?arnumber=10152477","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,14]],"date-time":"2024-03-14T04:26:35Z","timestamp":1710390395000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10152477\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12]]},"references-count":64,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tbme.2023.3280987","relation":{},"ISSN":["0018-9294","1558-2531"],"issn-type":[{"value":"0018-9294","type":"print"},{"value":"1558-2531","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12]]}}}