Spanish named entity recognition in the biomedical domain

Named Entity Recognition in the clinical domain and in languages different from English has the difficulty of the absence of complete dictionaries, the informality of texts, the polysemy of terms, the lack of accordance in the boundaries of an entity, the scarcity of corpora and of other resources a...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autor principal: Cotik, V.
Otros Autores: Rodríguez, H., Vivaldi, J., Alatrista-Salas H., Munante D., Lossio-Ventura J.A
Formato: Acta de conferencia Capítulo de libro
Lenguaje:Inglés
Publicado: Springer Verlag 2019
Acceso en línea:Registro en Scopus
DOI
Handle
Registro en la Biblioteca Digital
Aporte de:Registro referencial: Solicitar el recurso aquí
LEADER 10435caa a22008777a 4500
001 PAPER-25855
003 AR-BaUEN
005 20230518205800.0
008 190410s2019 xx ||||fo|||| 00| 0 eng|d
024 7 |2 scopus  |a 2-s2.0-85063486202 
040 |a Scopus  |b spa  |c AR-BaUEN  |d AR-BaUEN 
100 1 |a Cotik, V. 
245 1 0 |a Spanish named entity recognition in the biomedical domain 
260 |b Springer Verlag  |c 2019 
270 1 0 |m Cotik, V.; Department of Computer Science, FCEyN, Universidad de Buenos AiresArgentina; email: vcotik@dc.uba.ar 
506 |2 openaire  |e Política editorial 
504 |a Aleksovski, Z., (2014) Testing Radlex for Completeness Using Large Database of Radiology Reports, , Society for Imaging Informatics in Medicine, Annual Meeting 
504 |a Ambulódegui, E.S., (2012) Manual De Terminología Médica N 2 
504 |a Ananiadou, S., Friedman, C., Tsujii, J., Introduction: Named entity recognition in biomedicine (2004) J. Biomed. Inform., 37 (6), pp. 393-395 
504 |a Basaldella, M., Furrer, L., Tasso, C., Rinaldi, F., Entity recognition in the biomedical domain using a hybrid approach (2017) J. Biomed. Semant., 8 (1), p. 51 
504 |a Batista-Navarro, R.T., Rak, R., Ananiadou, S., Chemistry-specific features and heuristics for developing a CRF-based chemical named entity recogniser (2013) Proceedings of the Fourth Biocreative Challenge Evaluation Workshop, 2, pp. 55-59. , vol., pp., Citeseer 
504 |a Cascade, P.N., Berlin, L., Malpractice issues in radiology (1999) AJR Am. J. Roentgenol., 173 (6), pp. 1439-1442 
504 |a Castro, E., Iglesias, A., Martínez, P., Castaño, L., Automatic identification of biomedical concepts in Spanish-language unstructured clinical texts (2010) Proceedings of the 1St ACM International Health Informatics Symposium, pp. 751-757. , pp., ACM 
504 |a Chapman, W.W., Cohen, K.B., Current issues in biomedical text mining and natural language processing (2009) J. Biomed. Inform., 42 (5), pp. 757-759 
504 |a Chinchor, N., Hirschman, L., Lewis, D.D., Evaluating message understanding systems: An analysis of the third message understanding conference (MUC-3) (1993) Assoc. Comput. Linguist., 19 (3), pp. 409-449 
504 |a Cohen, A.M., Hersh, W.R., A survey of current work in biomedical text mining (2005) Brief. Bioinform., 6 (1), pp. 57-71 
504 |a Cotik, V., Filippo, D., Roller, R., Uszkoreit, H., Xu, F., Annotation of entities and relations in Spanish radiology reports (2017) In: Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP, 2017, pp. 177-184. , pp 
504 |a Do, B., Wu, A., Maley, J., Biswal, S., Automatic retrieval of bone fracture knowledge using natural language processing (2013) J. Digit. Imaging, 26 (4), pp. 709-713 
504 |a Iglesias, A., Mostas: Un etiquetador morfo-semántico, anonimizador y corrector de historiales clínicos (2008) Procesamiento Del Lenguaje Nat, 41, pp. 299-300 
504 |a Jiang, J., Guan, Y., Zhao, C., WI-ENRE in CLEF eHealth evaluation lab 2015: Clinical named entity recognition based on CRF (2015) Working Notes of CLEF 2015-Conference and Labs of the Evaluation Forum, Toulouse, France 
504 |a López Piñero, J.M., Terrada Ferrandis, M.L., (2005) Introducción a La terminología médica, , Masson S.A 
504 |a Laguna, J.Y., Diccionario De Siglas médicas Y Otras Abreviaturas, epónimos Y términos médicos Relacionados Con La codificación De Las Altas Hospitalarias 
504 |a Lakhani, P., Langlotz, C.P., Automated detection of radiology reports that document non-routine communication of critical or significant results (2009) J. Digit. Imaging, 23 (6), pp. 647-657 
504 |a Leaman, R., Gonzalez, G., BANNER: An executable survey of advances in biomedical named entity recognition (2008) Proceedings of the Pacific Symposium on Bio-Computing, 13, pp. 652-663. , vol., pp 
504 |a Moon, S., Pakhomov, S.V.S., Liu, N., Ryan, J.O., Melton, G.B., A sense inventory for clinical abbreviations and acronyms created using clinical notes and medical dictionary resources (2014) JAMIA, 21 (2), pp. 299-307 
504 |a Nadeau, D., Sekine, S., A survey of named entity recognition and classification (2007) Linguist. Investig., 30 (1), pp. 3-26. , https://doi.org/10.1075/li.30.1.03nad 
504 |a Oronoz, M., Casillas, A., Gojenola, K., Perez, A., Automatic annotation of medical records in Spanish with disease, drug and substance names (2013) CIARP 2013. LNCS, 8259, pp. 536-543. , https://doi.org/10.1007/978-3-642-41827-367, Ruiz-Shulcloper, J., Sanniti di Baja, G. (eds.), pp., Springer, Heidelberg 
504 |a Poibeau, T., Kosseim, L., Proper name extraction from non-journalistic texts (2000) In: Computational Linguistics in the Netherlands 2000, Selected Papers from the Eleventh CLIN Meeting, Tilburg, 3, pp. 144-157. , November, pp 
504 |a Roller, R., Detecting named entities and relations in German clinical reports (2018) GSCL 2017. LNCS (LNAI), 10713, pp. 146-154. , https://doi.org/10.1007/978-3-319-73706-512, Rehm, G., Declerck, T. (eds.) 
504 |a Santiso, S., Casillas, A., Pérez, A., Oronoz, M., Medical entity recognition and negation extraction: Assessment of NegEx on health records in Spanish (2017) IWBBIO 2017. LNCS, 10208, pp. 177-188. , https://doi.org/10.1007/978-3-319-56148-615, Rojas, I., Ortuño, F. (eds.), pp., Springer, Cham 
504 |a Settles, B., Biomedical named entity recognition using conditional random fields and rich feature sets (2004) Proceedings of the COLING 2004 International Joint Workshop on Natural Language Processing in Biomedicine and Its Applications (Nlpba/Bionlp), COLING, p. 2004. , Association for Computational Linguistics, Stroudsburg 
504 |a Shen, D., Zhang, J., Zhou, G., Su, J., Tan, C.L., Effective adaptation of a hidden Markov model-based named entity recognizer for biomedical domain (2003) Proceedings of the ACL 2003 Workshop on Natural Language Processing in Biomedicine, 13, pp. 49-56. , Association for Computational Linguistics 
504 |a Simpson, M.S., Demner-Fushman, D., (2012) Biomedical Text Mining: A Survey of Recent Progress, pp. 465-517. , https://doi.org/10.1007/978-1-4614-3223-414, Aggarwal, C., Zhai, C. (eds.) Mining Text Data, pp., Springer, Boston 
504 |a Sondhi, P., (2008) A Survey on Named Entity Extraction in the Biomedical Domain 
504 |a Takeuchi, K., Collier, N., Bio-medical entity extraction using support vector machines (2005) Artif. Intell. Med., 33 (2), pp. 125-137 
504 |a Tasneem, A., Archana, B., A survey on biomedical named entity extraction Asian 
504 |a (2016) J. Eng. Technol. Innov., 4 (7), pp. 25-28 
504 |a Uzuner, Ö., Solti, I., Cadag, E., Extracting medication information from clinical text (2010) J. Am. Med. Inform. Assoc., 17 (5), pp. 514-518 
504 |a Estopà, R., Vivaldi, J., Cabré, M.T., Use of Greek and Latin forms for term detection (2000) Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC 2000), 78, pp. 855-859. , vol., pp 
504 |a Weegar, R., Casillas, A., de Ilarraza, A.D., Oronoz, M., Prez, A., Gojenola, K., The impact of simple feature engineering in multilingual medical NER (2016) Proceedings of the Clinical Natural Language Processing Workshop, pp. 1-6. , pp 
504 |a Xu, H., Stetson, P.D., Friedman, C., A study of abbreviations in clinical notes (2007) AMIA 2007, American Medical Informatics Association Annual Symposium, , Chicago, IL, USAA4 - BBVA, Peru; North American Chapter of the ACL, USA; Telefónica del Perú, Peru 
520 3 |a Named Entity Recognition in the clinical domain and in languages different from English has the difficulty of the absence of complete dictionaries, the informality of texts, the polysemy of terms, the lack of accordance in the boundaries of an entity, the scarcity of corpora and of other resources available. We present a Named Entity Recognition method for poorly resourced languages. The method was tested with Spanish radiology reports and compared with a conditional random fields system. © 2019, Springer Nature Switzerland AG.  |l eng 
536 |a Detalles de la financiación: National Academy of Medicine 
536 |a Detalles de la financiación: http://www.redsamid.net/archivos/201612/diccionario-de-siglas-medicas.pdf?0 
536 |a Detalles de la financiación: 9 The paper is not available online. Results were discussed in a personal communica-tion. 10 In Spanish they usually occur before the terms of interest. 11Acronyms and abbreviations provided by the National Academy of Medicine of Colombia http://dic.idiomamedico.net/Siglas y abreviaturas and by the Span-ish Ministry of Health http://www.redsamid.net/archivos/201612/diccionario-de-siglas-medicas.pdf?0. 
593 |a Department of Computer Science, FCEyN, Universidad de Buenos Aires, Buenos Aires, Argentina 
593 |a Polytechnical University of Catalonia, Barcelona, Spain 
593 |a Universitat Pompeu Fabra, Barcelona, Spain 
690 1 0 |a BIONLP 
690 1 0 |a NAMED ENTITY RECOGNITION 
690 1 0 |a RADIOLOGY REPORTS 
690 1 0 |a SPANISH 
700 1 |a Rodríguez, H. 
700 1 |a Vivaldi, J. 
700 1 |a Alatrista-Salas H. 
700 1 |a Munante D. 
700 1 |a Lossio-Ventura J.A. 
711 2 |d 3 September 2018 through 5 September 2018  |g Código de la conferencia: 223899 
773 0 |d Springer Verlag, 2019  |g v. 898  |h pp. 233-248  |p Commun. Comput. Info. Sci.  |n Communications in Computer and Information Science  |x 18650929  |z 9783030116798  |t 5th International Conference on Information Management and Big Data, SIMBig 2018 
856 4 1 |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063486202&doi=10.1007%2f978-3-030-11680-4_23&partnerID=40&md5=b6eb6c13ecf7067e268f15e44c33453c  |y Registro en Scopus 
856 4 0 |u https://doi.org/10.1007/978-3-030-11680-4_23  |y DOI 
856 4 0 |u https://hdl.handle.net/20.500.12110/paper_18650929_v898_n_p233_Cotik  |y Handle 
856 4 0 |u https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_18650929_v898_n_p233_Cotik  |y Registro en la Biblioteca Digital 
961 |a paper_18650929_v898_n_p233_Cotik  |b paper  |c PE 
962 |a info:eu-repo/semantics/article  |a info:ar-repo/semantics/artículo  |b info:eu-repo/semantics/publishedVersion 
999 |c 86808