Výsledky vyhledávání - "Jenny Copara"

Akademický článek

Ensemble of Deep Masked Language Models for Effective Named Entity Recognition in Health and Life Science Corpora

Autor: Nona Naderi, Julien Knafou, Jenny Copara, Patrick Ruch, Douglas Teodoro

Publikováno v: Frontiers in Research Metrics and Analytics, Vol 6 (2021)

The health and life science domains are well known for their wealth of named entities found in large free text corpora, such as scientific literature and electronic health records. To unlock the value of such corpora, named entity recognition (NER) m

Externí odkaz: https://doaj.org/article/6ac0fcb24105417990a9ab076b52233a

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Akademický článek

Information Retrieval in an Infodemic: The Case of COVID-19 Publications

Autor: Douglas Teodoro, Sohrab Ferdowsi, Nikolay Borissov, Elham Kashani, David Vicente Alvarez, Jenny Copara, Racha Gouareb, Nona Naderi, Poorya Amini

Publikováno v: Journal of Medical Internet Research, Vol 23, Iss 9, p e30161 (2021)

BackgroundThe COVID-19 global health crisis has led to an exponential surge in published scientific literature. In an attempt to tackle the pandemic, extremely large COVID-19–related corpora are being created, sometimes with inaccurate information,

Externí odkaz: https://doaj.org/article/cba849c742e04910a85f0f0de52fc941

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On Graph Construction for Classification of Clinical Trials Protocols Using Graph Neural Networks

Autor: Sohrab Ferdowsi, Jenny Copara, Racha Gouareb, Nikolay Borissov, Fernando Jaume-Santero, Poorya Amini, Douglas Teodoro

Publikováno v: Artificial Intelligence in Medicine ISBN: 9783031093418

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5e072839b57ea077a6f1fa71af2d1c77
https://doi.org/10.1007/978-3-031-09342-5_24

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Information Retrieval in an Infodemic: The Case of COVID-19 Publications (Preprint)

Autor: Douglas Teodoro, Sohrab Ferdowsi, Nikolay Borissov, Elham Kashani, David Vicente Alvarez, Jenny Copara, Racha Gouareb, Nona Naderi, Poorya Amini

BACKGROUND The COVID-19 global health crisis has led to an exponential surge in published scientific literature. In an attempt to tackle the pandemic, extremely large COVID-19–related corpora are being created, sometimes with inaccurate information

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::853ca18ca8d0076478db457f36fbec96
https://doi.org/10.2196/preprints.30161

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Ensemble of deep masked language models for effective named entity recognition in multi-domain corpora

Autor: Patrick Ruch, Julien Knafou, Douglas Teodoro, Jenny Copara, Nona Naderi

The health and life science domains are well known for their wealth of entities. These entities are presented as free text in large corpora, such as biomedical scientific and electronic health records. To enable the secondary use of these corpora and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::43e450ee38010f6e4c831b77bc7f5187
https://doi.org/10.1101/2021.04.26.21256038

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Information retrieval in an infodemic: the case of COVID-19 publications

Autor: Nikolay Borissov, Sohrab Ferdowsi, Douglas Teodoro, Poorya Amini, Jenny Copara, Racha Gouareb, David Vicente Alvarez, Elham Kashani, Nona Naderi

Publikováno v: Journal of Medical Internet Research
Teodoro, Douglas; Ferdowsi, Sohrab; Borissov, Nikolay; Kashani, Elham; Vicente Alvarez, David; Copara, Jenny; Gouareb, Racha; Naderi, Nona; Amini, Poorya (2021). Information retrieval in an infodemic: the case of COVID-19 publications. Journal of medical internet research, 23(9), e30161. Centre of Global eHealth Innovation 10.2196/30161
JMIR. Journal of medical internet research, Vol. 23, No 9 (2021) P. e30161

Background The COVID-19 global health crisis has led to an exponential surge in published scientific literature. In an attempt to tackle the pandemic, extremely large COVID-19–related corpora are being created, sometimes with inaccurate information

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d924421e0d2b2577f65b409f3eba5e0f

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Contextualized French Language Models for Biomedical Named Entity Recognition

Autor: Jenny Copara, Julien Knafou, Nona Naderi, Claudia Moro, Patrick Ruch, Douglas Teodoro

Publikováno v: Actes de la 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Atelier DÉfi Fouille de Textes
6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Atelier DÉfi Fouille de Textes
6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Atelier DÉfi Fouille de Textes, 2020, Nancy, France. pp.36-48
HAL
Actes de la 6e conférence conjointe Journées d'Études sur la Parole (JEP, 31e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Atelier DÉfi Fouille de Textes
6e conférence conjointe Journées d'Études sur la Parole (JEP, 31e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition)
6e conférence conjointe Journées d'Études sur la Parole (JEP, 31e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition), 2020, Nancy, France. pp.36-48
Actes de la 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Atelier DÉfi Fouille de Textes pp. 36-48

Named entity recognition (NER) is key for biomedical applications as it allows knowledge discovery in free text data. As entities are semantic phrases, their meaning is conditioned to the context to avoid ambiguity. In this work, we explore contextua

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::53ac078ec78a2f0375847e3bfd45334a
https://hal.archives-ouvertes.fr/hal-02784740/file/215.pdf

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BioBERTpt - A Portuguese Neural Language Model for Clinical Named Entity Recognition

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

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

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BiTeM at WNUT 2020 Shared Task-1: Named Entity Recognition over Wet Lab Protocols using an Ensemble of Contextual Language Models

Autor: Douglas Teodoro, Julien Knafou, Patrick Ruch, Nona Naderi, Jenny Copara

Publikováno v: Proceedings of the 2020 EMNLP Workshop W-NUT: The Sixth Workshop on Noisy User-generated Text pp. 305-313
W-NUT@EMNLP

Recent improvements in machine-reading technologies attracted much attention to automation problems and their possibilities. In this context, WNUT 2020 introduces a Name Entity Recognition (NER) task based on wet laboratory procedures. In this paper,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::540784afea0a9b87ac4dbbc1d9f248ab
https://archive-ouverte.unige.ch/unige:159575

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Conditional Random Fields for Spanish Named Entity Recognition Using Unsupervised Features

Autor: José Luis Ochoa, Camilo Thorne, Jenny Copara, Goran Glavaš

Publikováno v: Lecture Notes in Computer Science ISBN: 9783319479545
IBERAMIA

Unsupervised features based on word representations such as word embeddings and word collocations have shown to significantly improve supervised NER for English. In this work we investigate whether such unsupervised features can also boost supervised

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::400557fcac81f0db93d3bcc11508aa60
https://doi.org/10.1007/978-3-319-47955-2_15

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