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Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing.
Grabar, Natalia; Grouin, Cyril.
  • Grabar N; Université Paris Saclay, CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique, Orsay, France.
  • Grouin C; STL, CNRS, Université de Lille, Domaine du Pont-de-bois, Villeneuve-d'Ascq cedex, France.
Yearb Med Inform ; 30(1): 257-263, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1392950
ABSTRACT

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.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Natural Language Processing / Social Networking / COVID-19 Type of study: Observational study / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: Yearb Med Inform Year: 2021 Document Type: Article Affiliation country: S-0041-1726528

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Natural Language Processing / Social Networking / COVID-19 Type of study: Observational study / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: Yearb Med Inform Year: 2021 Document Type: Article Affiliation country: S-0041-1726528