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Evaluating the use of large language model in identifying top research questions in gastroenterology

The field of gastroenterology (GI) is constantly evolving. It is essential to pinpoint the most pressing and important research questions. To evaluate the potential of chatGPT for identifying research priorities in GI and provide a starting point for further investigation. We queried chatGPT on four...

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Autores principales: Lahat, Adi, Shachar, Eyal, Avidan, Benjamin, Shatz, Zina, Glicksberg, Benjamin S., Klang, Eyal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10011374/
https://www.ncbi.nlm.nih.gov/pubmed/36914821
http://dx.doi.org/10.1038/s41598-023-31412-2
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author Lahat, Adi
Shachar, Eyal
Avidan, Benjamin
Shatz, Zina
Glicksberg, Benjamin S.
Klang, Eyal
author_facet Lahat, Adi
Shachar, Eyal
Avidan, Benjamin
Shatz, Zina
Glicksberg, Benjamin S.
Klang, Eyal
author_sort Lahat, Adi
collection PubMed
description The field of gastroenterology (GI) is constantly evolving. It is essential to pinpoint the most pressing and important research questions. To evaluate the potential of chatGPT for identifying research priorities in GI and provide a starting point for further investigation. We queried chatGPT on four key topics in GI: inflammatory bowel disease, microbiome, Artificial Intelligence in GI, and advanced endoscopy in GI. A panel of experienced gastroenterologists separately reviewed and rated the generated research questions on a scale of 1–5, with 5 being the most important and relevant to current research in GI. chatGPT generated relevant and clear research questions. Yet, the questions were not considered original by the panel of gastroenterologists. On average, the questions were rated 3.6 ± 1.4, with inter-rater reliability ranging from 0.80 to 0.98 (p < 0.001). The mean grades for relevance, clarity, specificity, and originality were 4.9 ± 0.1, 4.6 ± 0.4, 3.1 ± 0.2, 1.5 ± 0.4, respectively. Our study suggests that Large Language Models (LLMs) may be a useful tool for identifying research priorities in the field of GI, but more work is needed to improve the novelty of the generated research questions.
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spelling pubmed-100113742023-03-15 Evaluating the use of large language model in identifying top research questions in gastroenterology Lahat, Adi Shachar, Eyal Avidan, Benjamin Shatz, Zina Glicksberg, Benjamin S. Klang, Eyal Sci Rep Article The field of gastroenterology (GI) is constantly evolving. It is essential to pinpoint the most pressing and important research questions. To evaluate the potential of chatGPT for identifying research priorities in GI and provide a starting point for further investigation. We queried chatGPT on four key topics in GI: inflammatory bowel disease, microbiome, Artificial Intelligence in GI, and advanced endoscopy in GI. A panel of experienced gastroenterologists separately reviewed and rated the generated research questions on a scale of 1–5, with 5 being the most important and relevant to current research in GI. chatGPT generated relevant and clear research questions. Yet, the questions were not considered original by the panel of gastroenterologists. On average, the questions were rated 3.6 ± 1.4, with inter-rater reliability ranging from 0.80 to 0.98 (p < 0.001). The mean grades for relevance, clarity, specificity, and originality were 4.9 ± 0.1, 4.6 ± 0.4, 3.1 ± 0.2, 1.5 ± 0.4, respectively. Our study suggests that Large Language Models (LLMs) may be a useful tool for identifying research priorities in the field of GI, but more work is needed to improve the novelty of the generated research questions. Nature Publishing Group UK 2023-03-13 /pmc/articles/PMC10011374/ /pubmed/36914821 http://dx.doi.org/10.1038/s41598-023-31412-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Lahat, Adi
Shachar, Eyal
Avidan, Benjamin
Shatz, Zina
Glicksberg, Benjamin S.
Klang, Eyal
Evaluating the use of large language model in identifying top research questions in gastroenterology
title Evaluating the use of large language model in identifying top research questions in gastroenterology
title_full Evaluating the use of large language model in identifying top research questions in gastroenterology
title_fullStr Evaluating the use of large language model in identifying top research questions in gastroenterology
title_full_unstemmed Evaluating the use of large language model in identifying top research questions in gastroenterology
title_short Evaluating the use of large language model in identifying top research questions in gastroenterology
title_sort evaluating the use of large language model in identifying top research questions in gastroenterology
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10011374/
https://www.ncbi.nlm.nih.gov/pubmed/36914821
http://dx.doi.org/10.1038/s41598-023-31412-2
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