ABSTRACT
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.
Subject(s)
COVID-19 , Natural Language Processing , Humans , Information Storage and Retrieval , Social NetworkingABSTRACT
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.