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20 results on '"Moro, Claudia"'

3. De-Identification Challenges in Real-World Portuguese Clinical Texts

Author

Prado, Carolina Braun, Gumiel, Yohan Bonescki, Schneider, Elisa Terumi Rubel, Cintho, Lilian Mie Mukai, de Souza, João Vitor Andrioli, Oliveira, Lucas Emanuel Silva e, Paraiso, Emerson Cabrera, Rebelo, Marina Sa, Gutierrez, Marco Antonio, Pires, Fabio Antero, Krieger, José Eduardo, Moro, Claudia, Magjarević, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, Marques, Jefferson Luiz Brum, editor, Rodrigues, Cesar Ramos, editor, Suzuki, Daniela Ota Hisayasu, editor, Marino Neto, José, editor, and García Ojeda, Renato, editor

Published
2024
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7. Challenges in Annotating a Treebank of Clinical Narratives in Brazilian Portuguese

Author

de Oliveira, Lucas Ferro Antunes, Pagano, Adriana, e Oliveira, Lucas Emanuel Silva, Moro, Claudia, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Pinheiro, Vládia, editor, Gamallo, Pablo, editor, Amaro, Raquel, editor, Scarton, Carolina, editor, Batista, Fernando, editor, Silva, Diego, editor, Magro, Catarina, editor, and Pinto, Hugo, editor

Published
2022
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11. Abstract 10990: The Prognostic Significance of Right Ventricular Dilation Assessed by Cardiac Magnetic Resonance Imaging in Heart Failure With Reduced Ejection Fraction

Author

Malkawi, Abdallah, Altibi, Ahmed, Mansour, Munthir, Schwitter, Juerg, Guaricci, Andrea, Masci, Pier-Giorgio, De Cecco, Carlo, Carrabba, Nazario, Varga-Szemes, Akos, Masi, Ambra, Baggiano, Andrea, Barison, Andrea, lanzillo, chiara, Martini, Chiara, moro, claudia, Andreini, Daniele, Conte, Edoardo, Rabbat, Mark, Focardi, Marta, Perazzolo Marra, Martina, Lombardi, Massimo, Dobrovie, Monica, Gaibazzi, Nicola, PEDROTTI, PATRIZIA, Schoepf, Joseph, Mushtaq, Saima, Censi, Stefano, Tat, Emily, Bogaert, Jan, Lozano Torres, Jordi, Sverzellati, Nicola, Marco, Guglielmo, Gismondi, Annalaura, Gravina, Matteo, Presicci, Cristina, De Lazzari, Manuel, Palumbo, Alessandro, Valentini, Adele, Di Giovine, Gabriella, Fusini, Laura, Margonato, Davide, Timpani, Mauro, Nese, Alberto, Pepi, Mauro, Cicala, Gloria, Muscogiuri, Giuseppe, Lorenzoni, Valentina, Pontone, Gianluca, and AlʼAref, Subhi J

Published
2022
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12. Prediction of the occurrence of leprosy reactions based on Bayesian networks

Author

de Andrade Rodrigues, Rafael Saraiva, primary, Heise, Eduardo Ferreira José, additional, Hartmann, Luis Felipe, additional, Rocha, Guilherme Eduardo, additional, Olandoski, Marcia, additional, de Araújo Stefani, Mariane Martins, additional, Latini, Ana Carla Pereira, additional, Soares, Cleverson Teixeira, additional, Belone, Andrea, additional, Rosa, Patrícia Sammarco, additional, de Andrade Pontes, Maria Araci, additional, de Sá Gonçalves, Heitor, additional, Cruz, Rossilene, additional, Penna, Maria Lúcia Fernandes, additional, Carvalho, Deborah Ribeiro, additional, Fava, Vinicius Medeiros, additional, Bührer-Sékula, Samira, additional, Penna, Gerson Oliveira, additional, Moro, Claudia Maria Cabral, additional, Nievola, Julio Cesar, additional, and Mira, Marcelo Távora, additional

Published
2023
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15. CardioBERTpt: Transformer-based Models for Cardiology Language Representation in Portuguese

Author

Schneider, Elisa Terumi Rubel, primary, Gumiel, Yohan Bonescki, additional, de Souza, João Vitor Andrioli, additional, Mie Mukai, Lilian, additional, Emanuel Silva e Oliveira, Lucas, additional, de Sa Rebelo, Marina, additional, Antonio Gutierrez, Marco, additional, Eduardo Krieger, Jose, additional, Teodoro, Douglas, additional, Moro, Claudia, additional, and Paraiso, Emerson Cabrera, additional

Published
2023
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16. Temporal Relation Extraction in Clinical Texts

Author

Gumiel, Yohan Bonescki, Silva E Oliveira, Lucas Emanuel, Claveau, Vincent, Grabar, Natalia, Paraiso, Emerson Cabrera, Moro, Claudia, Carvalho, Deborah Ribeiro, Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Université pontificale catholique du Paraná/Pontifícia Universidade Católica do Paraná [Curitiba, PR, Brazil], Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Creating and exploiting explicit links between multimedia fragments (LinkMedia), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-MEDIA ET INTERACTIONS (IRISA-D6), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Savoirs, Textes, Langage (STL) - UMR 8163 (STL), Université de Lille-Centre National de la Recherche Scientifique (CNRS), Pontifícia Universidade Católica do Paraná (PUCPR), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAL, IMAGE ET LANGAGE (IRISA-D6), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), and Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique)

Subjects
[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

International audience; Unstructured data in electronic health records, represented by clinical texts, are a vast source of healthcare information because they describe a patient's journey, including clinical findings, procedures, and information about the continuity of care. The publication of several studies on temporal relation extraction from clinical texts during the last decade and the realization of multiple shared tasks highlight the importance of this research theme. Therefore, we propose a review of temporal relation extraction in clinical texts. We analyzed 105 articles and verified that relations between events and document creation time, a coarse temporality type, were addressed with traditional machine learning–based models with few recent initiatives to push the state-of-the-art with deep learning–based models. For temporal relations between entities (event and temporal expressions) in the document, factors such as dataset imbalance because of candidate pair generation and task complexity directly affect the system's performance. The state-of-the-art resides on attention-based models, with contextualized word representations being fine-tuned for temporal relation extraction. However, further experiments and advances in the research topic are required until real-time clinical domain applications are released. Furthermore, most of the publications mainly reside on the same dataset, hindering the need for new annotation projects that provide datasets for different medical specialties, clinical text types, and even languages.

Published
2022
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17. Prediction of the Occurrence of Leprosy Reactions Based on Bayesian Networks

Author

Rodrigues, Rafael Saraiva de Andrade, primary, Heise, Eduardo Ferreira José, additional, Hartmann, Luis Felipe, additional, Rocha, Guilherme Eduardo, additional, Olandoski, Marcia, additional, Stefani, Mariane Martins de Araújo, additional, Latini, Ana Carla Pereira, additional, Soares, Cleverson Teixeira, additional, Belone, Andrea, additional, Rosa, Patrícia Sammarco, additional, Pontes, Maria Araci de Andrade, additional, Gonçalves, Heitor de Sá, additional, Cruz, Rossilene, additional, Penna, Maria Lúcia Fernandes, additional, Carvalho, Deborah Ribeiro, additional, Fava, Vinicius Medeiros, additional, Bührer-Sékula, Samira, additional, Penna, Gerson Oliveira, additional, Moro, Claudia Maria Cabral, additional, Nievola, Julio Cesar, additional, and Mira, Marcelo Távora, additional

Published
2022
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19. 'Quer N0 AVC' for Monitoring Stroke Patients' Healthcare Using a Mobile App.

Author

dos Santos LEANDRO, Gabrielle, BITTENCOURT, Ivonei, NAGEL, Vivian, Cabral MORO, Carla Heloisa, and MORO, Claudia

Abstract

Stroke is one of the leading causes of death and impairments worldwide. After hospital discharge, it is necessary to monitor these patients during their recovery. This research addresses the implementation of a mobile app, entitled 'Quer N0 AVC', to improve the quality of stroke patient care in Joinville, Brazil. The study method was divided into two parts. The adaptation phase included all the necessary information in the app for monitoring stroke patients. The implementation phase aimed to prepare a routine for the Quer mobile app installation. One of the questionnaires collected data from 42 patients and identified that before hospital admission 29% of them did not have medical appointments, 36% had one or two appointments, 11% had three appointments, and 24% had four or more appointments. This research portrayed adaptation feasibility and the implementation of a cell phone app for following up on stroke patients. [ABSTRACT FROM AUTHOR]

Published
2023
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20. Temporal Relation Extraction in Clinical Texts: A Systematic Review.

Author

BONESCKI GUMIEL, YOHAN, SILVA EOLIVEIRA, LUCAS EMANUEL, CLAVEAU, VINCENT, GRABAR, NATALIA, CABRERA PARAISO, EMERSON, MORO, CLAUDIA, and RIBEIRO CARVALHO, DEBORAH

Subjects
DEEP learning, ELECTRONIC health records, INFORMATION resources, NATURAL language processing, CONTINUUM of care, MEDICAL specialties & specialists, DOCUMENT clustering
Abstract

Unstructured data in electronic health records, represented by clinical texts, are a vast source of healthcare information because they describe a patient's journey, including clinical findings, procedures, and information about the continuity of care. The publication of several studies on temporal relation extraction from clinical texts during the last decade and the realization of multiple shared tasks highlight the importance of this research theme. Therefore, we propose a review of temporal relation extraction in clinical texts. We analyzed 105 articles and verified that relations between events and document creation time, a coarse temporality type, were addressed with traditional machine learning-based models with few recent initiatives to push the state-of-the-art with deep learning-based models. For temporal relations between entities (event and temporal expressions) in the document, factors such as dataset imbalance because of candidate pair generation and task complexity directly affect the system's performance. The state-of-the-art resides on attention-based models, with contextualized word representations being fine-tuned for temporal relation extraction. However, further experiments and advances in the research topic are required until real-time clinical domain applications are released. Furthermore, most of the publications mainly reside on the same dataset, hindering the need for new annotation projects that provide datasets for different medical specialties, clinical text types, and even languages. [ABSTRACT FROM AUTHOR]

Published
2022
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