Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Elisa Terumi Rubel"'
Autor:
Emerson Cabrera Paraiso, Yohan Bonescki Gumiel, Claudia Maria Cabral Moro, João Vitor Andrioli de Souza, Elisa Terumi Rubel Schneider
Publikováno v:
CBMS
Electronic health records (EHRs) contain patient-related information formed by structured and unstructured data, a valuable data source for Natural Language Processing (NLP) in the healthcare domain. The contextual word embeddings and Transformer-bas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e22ef87194d0b04fc32ac1af5207ec5
https://doi.org/10.1109/cbms52027.2021.00056
https://doi.org/10.1109/cbms52027.2021.00056
Autor:
Lucas Emanuel Silva e Oliveira, Mayara Aparecida Passaura da Luz, Yohan Bonescki Gumiel, Elisa Terumi Rubel Schneider, Claudia Maria Cabral Moro, Emerson Cabrera Paraiso
Publikováno v:
Intelligent Systems ISBN: 9783030916985
Question answering (QA) systems aim to answer human questions made in natural language. This type of functionality can be very useful in the most diverse application domains, such as the biomedical and clinical. Considering the clinical context, wher
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d753b1c4586671ceff8883ec8fa325e
https://doi.org/10.1007/978-3-030-91699-2_10
https://doi.org/10.1007/978-3-030-91699-2_10
Autor:
Julien Knafou, Elisa Terumi Rubel Schneider, Emerson Cabrera Paraiso, Lucas Ferro Antunes de Oliveira, Jenny Copara, Douglas Teodoro, João Vitor Andrioli de Souza, Yohan Bonescki Gumiel, Lucas Emanuel Silva e Oliveira, Claudia Maria Cabral Moro Barra
Publikováno v:
ClinicalNLP@EMNLP
Proceedings of the 3rd Clinical Natural Language Processing Workshop pp. 65-72
Proceedings of the 3rd Clinical Natural Language Processing Workshop pp. 65-72
With the growing number of electronic health record data, clinical NLP tasks have become increasingly relevant to unlock valuable information from unstructured clinical text. Although the performance of downstream NLP tasks, such as named-entity reco
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55b44f859509e35b921e79b70eb3eaa5
https://doi.org/10.18653/v1/2020.clinicalnlp-1.7
https://doi.org/10.18653/v1/2020.clinicalnlp-1.7
Autor:
de Souza, João Vitor Andrioli, Schneider, Elisa Terumi Rubel, Cezar, Josilaine Oliveira, Silva, Lucas Emanuel, Gumiel, Yohan Bonescki, Paraiso, Emerson, Teodoro, Douglas, Barra, Claudia Maria Cabral Moro
Publikováno v:
Journal of Health Informatics, Vol. 12 (2020) pp. 366-372
Objectives: Clinical Named Entity Recognition is a critical Natural Language Processing task, as it could support biomedical research and healthcare systems. While most extracted clinical entities are based on single-label concepts, it is very common
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1400::877e64af77c406f1bca1a97d1ea92740
https://archive-ouverte.unige.ch/unige:159572
https://archive-ouverte.unige.ch/unige:159572
Autor:
Michelly Alves Coutinho Gehlen, Elisa Terumi Rubel, Roberto Tadeu Raittz, Nilson Antônio da Rocha Coimbra, Fábio O. Pedrosa
Publikováno v:
BMC Bioinformatics
Background Azopirillum brasilense is a plant-growth promoting nitrogen-fixing bacteria that is used as bio-fertilizer in agriculture. Since nitrogen fixation has a high-energy demand, the reduction of N2 to NH4 + by nitrogenase occurs only under limi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::05d239150d790baa4ff247f0ffb33d2a
http://europepmc.org/articles/PMC5249018
http://europepmc.org/articles/PMC5249018