Year 2021: COVID-19, Information Extraction and BERTization among the Hottest Topics in Medical Natural Language Processing

Objectives : Analyze the content of publications within the medical natural language processing (NLP) domain in 2021. 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 : Four best pa...

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Detalles Bibliográficos
Autores principales: Grabar, Natalia, Grouin, Cyril
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Georg Thieme Verlag KG 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9719758/
https://www.ncbi.nlm.nih.gov/pubmed/36463883
http://dx.doi.org/10.1055/s-0042-1742547
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author Grabar, Natalia
Grouin, Cyril
author_facet Grabar, Natalia
Grouin, Cyril
author_sort Grabar, Natalia
collection PubMed
description Objectives : Analyze the content of publications within the medical natural language processing (NLP) domain in 2021. 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 : Four best papers have been selected in 2021. We also propose an analysis of the content of the NLP publications in 2021, all topics included. Conclusions : The main issues addressed in 2021 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 information extraction and use of information from social networks.
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spelling pubmed-97197582022-12-05 Year 2021: COVID-19, Information Extraction and BERTization among the Hottest Topics in Medical Natural Language Processing Grabar, Natalia Grouin, Cyril Yearb Med Inform Objectives : Analyze the content of publications within the medical natural language processing (NLP) domain in 2021. 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 : Four best papers have been selected in 2021. We also propose an analysis of the content of the NLP publications in 2021, all topics included. Conclusions : The main issues addressed in 2021 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 information extraction and use of information from social networks. Georg Thieme Verlag KG 2022-12-04 /pmc/articles/PMC9719758/ /pubmed/36463883 http://dx.doi.org/10.1055/s-0042-1742547 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 2021: COVID-19, Information Extraction and BERTization among the Hottest Topics in Medical Natural Language Processing
title Year 2021: COVID-19, Information Extraction and BERTization among the Hottest Topics in Medical Natural Language Processing
title_full Year 2021: COVID-19, Information Extraction and BERTization among the Hottest Topics in Medical Natural Language Processing
title_fullStr Year 2021: COVID-19, Information Extraction and BERTization among the Hottest Topics in Medical Natural Language Processing
title_full_unstemmed Year 2021: COVID-19, Information Extraction and BERTization among the Hottest Topics in Medical Natural Language Processing
title_short Year 2021: COVID-19, Information Extraction and BERTization among the Hottest Topics in Medical Natural Language Processing
title_sort year 2021: covid-19, information extraction and bertization among the hottest topics in medical natural language processing
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9719758/
https://www.ncbi.nlm.nih.gov/pubmed/36463883
http://dx.doi.org/10.1055/s-0042-1742547
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