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Text summarization with ChatGPT for drug labeling documents.

Authors :
Ying L
Liu Z
Fang H
Kusko R
Wu L
Harris S
Tong W
Source :
Drug discovery today [Drug Discov Today] 2024 Jun; Vol. 29 (6), pp. 104018. Date of Electronic Publication: 2024 May 07.
Publication Year :
2024

Abstract

Text summarization is crucial in scientific research, drug discovery and development, regulatory review, and more. This task demands domain expertise, language proficiency, semantic prowess, and conceptual skill. The recent advent of large language models (LLMs), such as ChatGPT, offers unprecedented opportunities to automate this process. We compared ChatGPT-generated summaries with those produced by human experts using FDA drug labeling documents. The labeling contains summaries of key labeling sections, making them an ideal human benchmark to evaluate ChatGPT's summarization capabilities. Analyzing >14000 summaries, we observed that ChatGPT-generated summaries closely resembled those generated by human experts. Importantly, ChatGPT exhibited even greater similarity when summarizing drug safety information. These findings highlight ChatGPT's potential to accelerate work in critical areas, including drug safety.<br /> (Published by Elsevier Ltd.)

Details

Language :
English
ISSN :
1878-5832
Volume :
29
Issue :
6
Database :
MEDLINE
Journal :
Drug discovery today
Publication Type :
Academic Journal
Accession number :
38723763
Full Text :
https://doi.org/10.1016/j.drudis.2024.104018