Year 2022 in Medical Natural Language Processing: Availability of Language Models as a Step in the Democratization of NLP in the Biomedical Area

Abstract

Objectives: To analyse the content of publications within the medical Natural Language Processing (NLP) domain in 2022. 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. We also propose an analysis of the content of the NLP publications in 2022, stressing on some of the topics. Conclusion: The main trend in 2022 is certainly related to the availability of large language models, especially those based on Transformers, and to their use by non-NLP researchers. This leads to the democratization of the NLP methods. We also observe the renewal of interest to languages other than English, the continuation of research on information extraction and prediction, the massive use of data from social media, and the consideration of needs and interests of patients.

Informatics for One Health

“…The authors presented numerous annotated datasets and various NLP tasks, with a strong emphasis on the use of pre-trained language models for these tasks. The synopsis of the NLP section, Cyril Grouin and Natalia Grabar, provides a comprehensive description of works published in 2022 [31]. After listing the languages studied in these recent works, they also underline the enthusiasm for large language models and note that the fact that most of them are freely available facilitates the democratization of NLP.…”