{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T09:33:06Z","timestamp":1781947986043,"version":"3.54.5"},"reference-count":51,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3131386","type":"journal-article","created":{"date-parts":[[2021,11,30]],"date-time":"2021-11-30T23:36:50Z","timestamp":1638315410000},"page":"159714-159723","source":"Crossref","is-referenced-by-count":15,"title":["DiLBERT: Cheap Embeddings for Disease Related Medical NLP"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-9191-3280","authenticated-orcid":false,"given":"Kevin","family":"Roitero","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-8887-616X","authenticated-orcid":false,"given":"Beatrice","family":"Portelli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0003-3378-0368","authenticated-orcid":false,"given":"Mihai Horia","family":"Popescu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-0144-3802","authenticated-orcid":false,"given":"Vincenzo Della","family":"Mea","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","first-page":"1","article-title":"Classifying German animal experiment summaries with multi-lingual BERT at CLEF eHealth 2019 task 1","author":"s\u00e4nger","year":"2019","journal-title":"Proc CLEF"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/825"},{"key":"ref33","article-title":"XLNet: Generalized autoregressive pretraining for language understanding","author":"yang","year":"2019","journal-title":"arXiv 1906 08237"},{"key":"ref32","article-title":"Cross-lingual language model pretraining","author":"lample","year":"2019","journal-title":"arXiv 1901 07291"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocz096"},{"key":"ref30","first-page":"1","article-title":"MLT-DFKI at CLEF eHealth 2019: Multi-label classification of ICD-10 codes with BERT","author":"amin","year":"2019","journal-title":"Proc CLEF"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2020.103607"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.2196\/14830"},{"key":"ref35","article-title":"DistilBERT, a distilled version of BERT: Smaller, faster, cheaper and lighter","author":"sanh","year":"2019","journal-title":"arXiv 1910 01108"},{"key":"ref34","article-title":"RoBERTa: A robustly optimized BERT pretraining approach","author":"liu","year":"2019","journal-title":"arXiv 1907 11692"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00051"},{"key":"ref27","first-page":"409","article-title":"Multi-label classification of patient notes: Case study on ICD code assignment","author":"baumel","year":"2017","journal-title":"Proc 32nd AAAI Conf Artif Intell"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocv032"},{"key":"ref1","first-page":"1","article-title":"Using deep learning for automatic ICD-10 classification from free-text data","volume":"16","author":"wang","year":"2020","journal-title":"Eur J Biomed Informat"},{"key":"ref20","first-page":"1","article-title":"CLEF eHealth 2018 multilingual information extraction task overview: ICD10 coding of death certificates in French, Hungarian and Italian","author":"n\u00e9v\u00e9ol","year":"2018","journal-title":"Proc CLEF"},{"key":"ref22","first-page":"1","article-title":"KCL-health-NLP CLEF eHealth 2018 task 1: ICD-10 coding of French and Italian death certificates with character-level convolutional neural networks","author":"ive","year":"2018","journal-title":"Proc CLEF"},{"key":"ref21","first-page":"1","article-title":"ECSTRA-APHP CLEF eHealth2018-task 1: ICD10 code extraction from death certificates","author":"flicoteaux","year":"2018","journal-title":"Proc CLEF"},{"key":"ref24","first-page":"1","article-title":"WBI at CLEF eHealth 2018 task 1: Language-independent ICD-10 coding using multi-lingual embeddings and recurrent neural networks","author":"seva","year":"2018","journal-title":"Proc CLEF"},{"key":"ref23","article-title":"Sequence to sequence learning with neural networks","author":"sutskever","year":"2014","journal-title":"arXiv 1409 3215 [cs]"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1098"},{"key":"ref25","first-page":"1","article-title":"IxaMed at CLEF eHealth 2018 task 1: ICD10 coding with a sequence-to-sequence approach","author":"atutxa","year":"2018","journal-title":"Proc CLEF"},{"key":"ref50","article-title":"The lottery ticket hypothesis for pre-trained BERT networks","author":"chen","year":"2020","journal-title":"arXiv 2007 12223"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.repl4nlp-1.18"},{"key":"ref10","year":"2016","journal-title":"International Statistical Classification of Diseases and Related Health Problems"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3442188.3445922"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.clinicalnlp-1.3"},{"key":"ref12","year":"2019","journal-title":"International Statistical Classification of Diseases and Related Health Problems"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3115\/1572392.1572416"},{"key":"ref14","first-page":"1","article-title":"Tlemcen university at CELF eHealth 2018 team techno: Multilingual information extraction-ICD10 coding","author":"bounaama","year":"2018","journal-title":"Proc CLEF"},{"key":"ref15","first-page":"1","article-title":"Instance-based learning for ICD10 categorization","volume":"2125","author":"gobeill","year":"2018","journal-title":"Proc Conf Labs Eval Forum"},{"key":"ref16","first-page":"649","article-title":"Character-level convolutional networks for text classification","author":"zhang","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1179"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.5772\/intechopen.91292"},{"key":"ref4","article-title":"Underlying cause of death identification from death certificates using reverse coding to text and a NLP based deep learning approach","volume":"21","author":"mea","year":"2020","journal-title":"Informat Med Unlocked"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1097\/QAI.0000000000001580"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-1202"},{"key":"ref5","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2019","journal-title":"arXiv 1810 04805"},{"key":"ref8","article-title":"Publicly available clinical BERT embeddings","author":"alsentzer","year":"2019","journal-title":"arXiv 1904 03323"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1031"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICPECA51329.2021.9362566"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btz682"},{"key":"ref46","article-title":"On the stability of fine-tuning BERT: Misconceptions, explanations, and strong baselines","author":"mosbach","year":"2020","journal-title":"arXiv 2006 04884"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1424"},{"key":"ref48","article-title":"Intermediate-task transfer learning with pretrained models for natural language understanding: When and why does it work?","author":"pruksachatkun","year":"2020","journal-title":"arXiv 2005 00628"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00349"},{"key":"ref42","article-title":"Google’s neural machine translation system: Bridging the gap between human and machine translation","author":"wu","year":"2016","journal-title":"arXiv 1609 08144"},{"key":"ref41","article-title":"PUBMED: The bibliographic database","author":"canese","year":"2013","journal-title":"The NCBI Handbook"},{"key":"ref44","first-page":"1","article-title":"CLEF eHealth 2017 multilingual information extraction task overview: ICD10 coding of death certificates in English and French","author":"n\u00e9v\u00e9ol","year":"2017","journal-title":"Proc CLEF eHealth Eval"},{"key":"ref43","year":"2011","journal-title":"Public Birth Period Linked Birth—Infant Death Birth Cohort Linked Birth—Infant Death Mortality Multiple Cause and Fetal Death Data Files are Available for Independent Research and Analyses"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/http\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09628010.pdf?arnumber=9628010","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,3,8]],"date-time":"2022-03-08T22:03:21Z","timestamp":1646777001000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/ieeexplore.ieee.org\/document\/9628010\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":51,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1109\/access.2021.3131386","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}