Information extraction of texts in the biomedical domain

Automatic detection of relevant terms in medical reports is useful for educational purposes and for clinical research. Natural language processing techniques can be applied in order to identify them. The main goal of this research is to develop a method to identify whether medical reports of imaging...

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Detalles Bibliográficos
Autor principal: Cotik, V.
Otros Autores: Wooldridge M., Yang Q., Alibaba.com; Department of Computer Science and Engineering at Universidad Nacional del Sur; Department of Computer Science at the School of Exact and Natural Sciences of Buenos Aires University; et al.; International Joint Conferences on Artificial Intelligence (IJCAI); Ministry of Science, Technology and Productive Innovation
Formato: Acta de conferencia Capítulo de libro
Lenguaje:Inglés
Publicado: International Joint Conferences on Artificial Intelligence 2015
Acceso en línea:Registro en Scopus
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Registro en la Biblioteca Digital
Aporte de:Registro referencial: Solicitar el recurso aquí
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100 1 |a Cotik, V. 
245 1 0 |a Information extraction of texts in the biomedical domain 
260 |b International Joint Conferences on Artificial Intelligence  |c 2015 
270 1 0 |m Cotik, V.; Computer Science Department, FCEyN, Universidad de Buenos AiresArgentina 
506 |2 openaire  |e Política editorial 
504 |a Aronson, A., A effective mapping of biomedical text to the umls metathesaurus: The metamap program (2001) Proc AMIA Symp, pp. 17-21 
504 |a Bretschneider, C., Zillner, S., Hammon, M., Identifying pathological findings in German radiology reports using a syntacto-semantic parsing approach (2013) Proc of Workshop on Biomedical Natural Language Processing, pp. 27-35 
504 |a Chapman, W.W., Wridewell, W., Hanbury, P., Cooper, G.F., Buchanan, B.G., A simple algorithm for identifying negated findings and diseases in discharge summaries (2001) Biomedical Informatics, 34 (5), pp. 301-310 
504 |a Chapman, W.W., Hilert, D., Velupillai, S., Kvist, M., Skeppstedt, M., Chapman, B.E., Conway, M., Deleger, L., Extending the negex lexicon for multiple languages (2013) Stud Health Technol Inform, 192, pp. 677-681 
504 |a Dang, P.A., Kalra, M.K., Schultz, T.J., Graham, S.A., Dreyer, K.J., Abbreviations: Application of recently developed computer algorithm for automatic classification of unstructured radiology reports (2005) Radiology, 234, pp. 323-329 
504 |a Dang, P.A., Kalra, M.K., Schultz, T.J., Graham, S.A., Dreyer, K.J., Informatics in radiology: Render: An online searchable radiology study repository (2009) Radiographics, 29 (5), pp. 1233-1246 
504 |a Do, B.H., Wu, A., Biswal, S., Kamaya, A., Rubin, D.L., Informatics in radiology: Radtf: A semantic search-enabled, natu-ral language processor-generated radiology teaching file (2010) Radiographics, 30 (7), pp. 2039-2048 
504 |a Gerstmair, A., Daumke, P., Simon, K., Langer, M., Kotter, E., Intelligent image retrieval based on radiology reports (2012) European Radiology, 22 (12), pp. 2750-2758 
504 |a Ramaswamy, M.R., Patterson, D.S., Yin, L., Goodacre, B.W., Mosearch: A radiologist-friendly tool for finding-based di-agnostic report and image retrieval (1996) Radiographics, 16 (4), pp. 923-933 
504 |a Skeppstedt, M., Negation detection in swedish clinical text: An adaption of negex to swedish (2011) Journal of Bio-medical Semantics, 2 (3), pp. 1-12 
504 |a Wu, A.S., Do, B.H., Kim, J., Rubin, D.L., Evaluation of negation and uncertainty detection and its impact on precision and recall in search (2011) Digital Imaging, 24 (2), pp. 234-242A4 - Alibaba.com; Department of Computer Science and Engineering at Universidad Nacional del Sur; Department of Computer Science at the School of Exact and Natural Sciences of Buenos Aires University; et al.; International Joint Conferences on Artificial Intelligence (IJCAI); Ministry of Science, Technology and Productive Innovation 
520 3 |a Automatic detection of relevant terms in medical reports is useful for educational purposes and for clinical research. Natural language processing techniques can be applied in order to identify them. The main goal of this research is to develop a method to identify whether medical reports of imaging studies (usually called radiology reports) written in Spanish are important (in the sense that they have non-negated pathological findings) or not. We also try to identify which finding is present and if possible its relationship with anatomical entities.  |l eng 
593 |a Computer Science Department, FCEyN, Universidad de Buenos Aires, Buenos Aires, Argentina 
690 1 0 |a ARTIFICIAL INTELLIGENCE 
690 1 0 |a MEDICAL IMAGING 
690 1 0 |a AUTOMATIC DETECTION 
690 1 0 |a BIOMEDICAL DOMAIN 
690 1 0 |a CLINICAL RESEARCH 
690 1 0 |a NATURAL LANGUAGE PROCESSING 
690 1 0 |a RADIOLOGY REPORTS 
690 1 0 |a RELEVANT TERMS 
690 1 0 |a NATURAL LANGUAGE PROCESSING SYSTEMS 
700 1 |a Wooldridge M. 
700 1 |a Yang Q. 
700 1 |a Alibaba.com; Department of Computer Science and Engineering at Universidad Nacional del Sur; Department of Computer Science at the School of Exact and Natural Sciences of Buenos Aires University; et al.; International Joint Conferences on Artificial Intelligence (IJCAI); Ministry of Science, Technology and Productive Innovation 
711 2 |d 25 July 2015 through 31 July 2015  |g Código de la conferencia: 116754 
773 0 |d International Joint Conferences on Artificial Intelligence, 2015  |g v. 2015-January  |h pp. 4357-4358  |p IJCAI Int. Joint Conf. Artif. Intell.  |n IJCAI International Joint Conference on Artificial Intelligence  |x 10450823  |z 9781577357384  |t 24th International Joint Conference on Artificial Intelligence, IJCAI 2015 
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