Titre :

Year 2023 in Biomedical Natural Language Processing: A Tribute to Large Language Models and Generative AI

Auteur(s) :

Grouin, Cyril [Auteur]
Laboratoire Interdisciplinaire des Sciences du Numérique [LISN]
Sciences et Technologies des Langues - LISN [STL]
Grabar, Natalia [Auteur]
Savoirs, Textes, Langage (STL) - UMR 8163 [STL]

Titre de la revue :

IMIA Yearbook of Medical Informatics

Éditeur :

Schattauer

Date de publication :

2024

ISSN :

0943-4747

Mot(s)-clé(s) en anglais :

Biomedical Natural Language Processing
Topics
Issues
Best Papers
2023

Discipline(s) HAL :

Informatique [cs]
Sciences du Vivant [q-bio]

Résumé en anglais : [en]

Objectives: this synopsis gives insights into scientific publications from 2023 in Natural Language Processing for the biomedical domain. We present the process we followed to identify candidates for NLP's best paper and ...
Lire la suite >Objectives: this synopsis gives insights into scientific publications from 2023 in Natural Language Processing for the biomedical domain. We present the process we followed to identify candidates for NLP's best paper and the two best papers of this year. We also analyze the current trends in the 2023 publications.Methods: we queried two databases (PubMed and the ACL anthology) and refined the outputs through automatic scoring. We then manually preselect publications to review and select candidate papers through an adjudication process. External reviewers assessed the interest of those 13 candidates. At last, the section editors chose the best NLP papers.Results: we collected 2,148 papers published in 2023, of which two were the best and selected as part of the NLP Chapter. Both address language models and propose solutions for data augmentation, domain-specific model adaptation, and model distillation. Work is done on social media content and electronic health records, using deep learning approaches such as ChatGPT and LLM.Conclusion: trends from 2023 cover classical NLP tasks (information extraction, text categorization, sentiment analysis), existing topics from several years (medical education), mainstream applications (ChatBot, generative approaches), and specific issues (cancer, COVID-19, mental health). Specifically for COVID-19, current researches deal with post-COVID-19 conditions (PCC), and they explore the understanding of how this pandemic has been managed and welcomed by populations. In addition, due to language models, a few works have been done to process languages other than English, especially using language portability approaches.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

• Savoirs, Textes, Langage (STL) - UMR 8163

Source :

Harvested from HAL