CC BY-NC-ND 4.0 · Yearb Med Inform 2020; 29(01): 221-225
DOI: 10.1055/s-0040-1701997
Section 10: Natural Language Processing
Georg Thieme Verlag KG Stuttgart

A Year of Papers Using Biomedical Texts:

Findings from the Section on Clinical Natural Language Processing of the International Medical Informatics Association Yearbook
Cyril Grouin
1  Université Paris-Saclay, CNRS, LIMSI, Orsay, France
Natalia Grabar
1  Université Paris-Saclay, CNRS, LIMSI, Orsay, France
2  STL, CNRS, Université de Lille, Villeneuve-d’Ascq, France
Section Editors for the IMIA Yearbook Section on Natural Language Processing› Author Affiliations
Further Information

Publication History

Publication Date:
21 August 2020 (online)


Objectives: Analyze papers published in 2019 within the medical natural language processing (NLP) domain in order to select the best works of the field.

Methods: We performed an automatic and manual pre-selection of papers to be reviewed and finally selected the best NLP papers of the year. We also propose an analysis of the content of NLP publications in 2019.

Results: Three best papers have been selected this year including the generation of synthetic record texts in Chinese, a method to identify contradictions in the literature, and the BioBERT word representation.

Conclusions: The year 2019 was very rich and various NLP issues and topics were addressed by research teams. This shows the will and capacity of researchers to move towards robust and reproducible results. Researchers also prove to be creative in addressing original issues with relevant approaches.