{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T23:17:55Z","timestamp":1787008675665,"version":"build-2736575974"},"reference-count":22,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T00:00:00Z","timestamp":1726444800000},"content-version":"vor","delay-in-days":259,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,9,16]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>This paper is a more in-depth analysis of the approaches used in our submission (Mart\u00ednez A, Garc\u00eda-Santa N. (2023) FRE @ BC8 SympTEMIST track: Named Entity Recognition Zenodo.) to the \u2018SympTEMIST\u2019 Named Entity Recognition (NER) shared subtask at \u2018BioCreative 2023\u2019. We participated on the challenge submitting two systems based on a RoBERTa architecture LLM trained on Spanish-language clinical data available at \u2018HuggingFace\u2019 model repository. Before choosing the systems that would be submitted, we tried different combinations of the techniques described here: Conditional Random Fields and Byte-Pair Encoding dropout. In the second system we also included Sub-Subword feature based embeddings (SSW). The test set used in the challenge has now been released (L\u00f3pez SL, S\u00e1nchez LG, Farr\u00e9 E et\u00a0al. (2024) SympTEMIST Corpus: Gold Standard annotations for clinical symptoms, signs and findings information extraction. Zenodo), allowing us to analyze more in depth our methods, as well as measuring the impact of introducing data from CARMEN-I (Lima-L\u00f3pez S, Farr\u00e9-Maduell E, Krallinger M. (2023) CARMEN-I: Clinical Entities Annotation Guidelines in Spanish. Zenodo) corpus. Our experiments show the moderate effect of using the Sub-Subword feature based embeddings and the impact of including the symptom NER data from the CARMEN-I dataset.<\/jats:p>\n                  <jats:p>Database URL: https:\/\/physionet.org\/content\/carmen-i\/1.0\/<\/jats:p>","DOI":"10.1093\/database\/baae101","type":"journal-article","created":{"date-parts":[[2024,8,30]],"date-time":"2024-08-30T14:47:34Z","timestamp":1725029254000},"source":"Crossref","is-referenced-by-count":2,"title":["An analysis of FRE @ BC8 SympTEMIST track: named entity recognition"],"prefix":"10.1093","volume":"2024","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2290-8194","authenticated-orcid":false,"given":"Ander","family":"Martinez","sequence":"first","affiliation":[{"name":"AI & Computing Research Group, Fujitsu Research of Europe Ltd , Camino del Cerro de los Gamos, 1, Pozuelo de Alarc\u00f3n, Madrid 28224, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3482-3297","authenticated-orcid":false,"given":"Nuria","family":"Garc\u00eda-Santa","sequence":"additional","affiliation":[{"name":"AI & Computing Research Group, Fujitsu Research of Europe Ltd , Camino del Cerro de los Gamos, 1, Pozuelo de Alarc\u00f3n, Madrid 28224, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,9,16]]},"reference":[{"key":"2024091613063881200_R1","article-title":"FRE @ BC8 SympTEMIST track: Named Entity Recognition","volume-title":"Zenodo","author":"Mart\u00ednez","year":"2023"},{"key":"2024091613063881200_R2","article-title":"SympTEMIST Corpus: Gold Standard annotations for clinical symptoms, signs and findings information extraction","volume-title":"Zenodo","author":"L\u00f3pez","year":"2024"},{"key":"2024091613063881200_R3","article-title":"CARMEN-I: clinical entities annotation guidelines in Spanish","volume-title":"Zenodo","author":"Lima-L\u00f3pez","year":"2023"},{"key":"2024091613063881200_R4","first-page":"184","article-title":"Named Entity Recognition using hundreds of thousands of features","author":"Mayfield","year":"2003"},{"key":"2024091613063881200_R5","doi-asserted-by":"publisher","first-page":"15","DOI":"10.5121\/ijnlc.2012.1402","article-title":"Named Entity Recognition using Hidden Markov Model (HMM)","volume":"1","author":"Morwal","year":"2012","journal-title":"Int J Nat Lang Comput"},{"key":"2024091613063881200_R6","article-title":"Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data","author":"Lafferty","year":"2001"},{"key":"2024091613063881200_R7","first-page":"363","article-title":"Incorporating non-local information into information extraction systems by Gibbs Sampling","author":"Finkel","year":"2005"},{"key":"2024091613063881200_R8","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-018-2467-9","article-title":"A multitask bi-directional RNN model for named entity recognition on Chinese electronic medical records","volume":"19","author":"Chowdhury","year":"2018","journal-title":"BMC Bioinf"},{"key":"2024091613063881200_R9","article-title":"BERT: pre-training of deep bidirectional transformers for language understanding","volume-title":"arXiv","author":"Devlin","year":"2019"},{"key":"2024091613063881200_R10","article-title":"RoBERTa: a robustly optimized BERT pretraining approach","volume-title":"arXiv","author":"Liu","year":"2019"},{"key":"2024091613063881200_R11","article-title":"Overview of Symptemist at Biocreative VIII: corpus, guidelines and evaluation of systems for the detection and normalization of symptoms, signs and findings from text","author":"Lima-L\u00f3pez","year":"2023"},{"key":"2024091613063881200_R12","article-title":"Text Chunking using Transformation-Based Learning","volume-title":"arXiv","author":"Ramshaw","year":"1995"},{"key":"2024091613063881200_R13","article-title":"Portuguese Named Entity Recognition using BERT-CRF","volume-title":"arXiv","author":"Souza","year":"2020"},{"key":"2024091613063881200_R14","doi-asserted-by":"crossref","DOI":"10.18653\/v1\/2020.acl-main.170","article-title":"BPE-Dropout: Simple and Effective Subword Regularization","volume-title":"arXiv","author":"Provilkov","year":"2020"},{"key":"2024091613063881200_R15","first-page":"66","article-title":"Subword regularization: improving neural network translation models with multiple subword candidates","author":"Kudo","year":"2018"},{"key":"2024091613063881200_R16","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1109\/TIT.1967.1054010","article-title":"Error bounds for convolutional codes and an asymptotically optimum decoding algorithm","volume":"13","author":"Viterbi","year":"1967","journal-title":"IEEE Trans Inf Theory"},{"key":"2024091613063881200_R17","article-title":"Neural Machine Translation of Rare Words with Subword Units","volume-title":"ArXiv150807909 Cs","author":"Sennrich","year":"2015"},{"key":"2024091613063881200_R18","doi-asserted-by":"crossref","first-page":"82","DOI":"10.5715\/jnlp.28.82","article-title":"Sub-subword N-gram features for subword-level neural machine translation","volume":"28","author":"Martinez","year":"2021","journal-title":"J Nat Lang Process"},{"key":"2024091613063881200_R19","first-page":"162","article-title":"The Fujitsu DMATH submissions for WMT21 news translation and biomedical translation tasks","author":"Martinez","year":"2021"},{"key":"2024091613063881200_R20","article-title":"Biomedical and clinical language models for Spanish: on the benefits of domain-specific pretraining in a mid-resource scenario","author":"Carrino","year":"2021"},{"key":"2024091613063881200_R21","article-title":"ICB-UMA at BioCreative VIII @ AMIA 2023 Task 2 SYMPTEMIST (symptom text mining shared task)","volume-title":"Zenodo","author":"Gallego","year":"2023"},{"key":"2024091613063881200_R22","article-title":"Team BIT.UA @ BC8 SympTEMIST track: a two-step pipeline for discovering and normalizing clinical symptoms in Spanish","author":"Jonker","year":"2023"}],"container-title":["Database"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/database\/article-pdf\/doi\/10.1093\/database\/baae101\/59140347\/baae101.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/database\/article-pdf\/doi\/10.1093\/database\/baae101\/59140347\/baae101.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T09:06:54Z","timestamp":1726477614000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/database\/article\/doi\/10.1093\/database\/baae101\/7758556"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1093\/database\/baae101","relation":{},"ISSN":["1758-0463"],"issn-type":[{"value":"1758-0463","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2024]]},"published":{"date-parts":[[2024]]},"article-number":"baae101"}}