Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing

Objectives: To analyze the content of publications within the medical NLP domain in 2020. Methods: Automatic and manual preselection of publications to be reviewed, and selection of the best NLP papers of the year. Analysis of the important issues. Results: Three best papers have been selected in 20...

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Autores principales: Grabar, Natalia, Grouin, Cyril
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Georg Thieme Verlag KG 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8416212/
https://www.ncbi.nlm.nih.gov/pubmed/34479397
http://dx.doi.org/10.1055/s-0041-1726528
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author Grabar, Natalia
Grouin, Cyril
author_facet Grabar, Natalia
Grouin, Cyril
author_sort Grabar, Natalia
collection PubMed
description Objectives: To analyze the content of publications within the medical NLP domain in 2020. Methods: Automatic and manual preselection of publications to be reviewed, and selection of the best NLP papers of the year. Analysis of the important issues. Results: Three best papers have been selected in 2020. We also propose an analysis of the content of the NLP publications in 2020, all topics included. Conclusion: The two main issues addressed in 2020 are related to the investigation of COVID-related questions and to the further adaptation and use of transformer models. Besides, the trends from the past years continue, such as diversification of languages processed and use of information from social networks
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spelling pubmed-84162122021-09-07 Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing Grabar, Natalia Grouin, Cyril Yearb Med Inform Objectives: To analyze the content of publications within the medical NLP domain in 2020. Methods: Automatic and manual preselection of publications to be reviewed, and selection of the best NLP papers of the year. Analysis of the important issues. Results: Three best papers have been selected in 2020. We also propose an analysis of the content of the NLP publications in 2020, all topics included. Conclusion: The two main issues addressed in 2020 are related to the investigation of COVID-related questions and to the further adaptation and use of transformer models. Besides, the trends from the past years continue, such as diversification of languages processed and use of information from social networks Georg Thieme Verlag KG 2021-08 2021-09-03 /pmc/articles/PMC8416212/ /pubmed/34479397 http://dx.doi.org/10.1055/s-0041-1726528 Text en IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.
spellingShingle Grabar, Natalia
Grouin, Cyril
Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing
title Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing
title_full Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing
title_fullStr Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing
title_full_unstemmed Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing
title_short Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing
title_sort year 2020 (with covid): observation of scientific literature on clinical natural language processing
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8416212/
https://www.ncbi.nlm.nih.gov/pubmed/34479397
http://dx.doi.org/10.1055/s-0041-1726528
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