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Evaluating the use of large language model in identifying top research questions in gastroenterology
by
Klang, Eyal
, Lahat, Adi
, Shatz, Zina
, Shachar, Eyal
, Avidan, Benjamin
, Glicksberg, Benjamin S.
in
631/114
/ 692/308
/ 692/4020
/ Artificial Intelligence
/ Endoscopy
/ Gastroenterologists
/ Gastroenterology
/ Humanities and Social Sciences
/ Humans
/ Inflammatory Bowel Diseases
/ Large language models
/ Microbiomes
/ multidisciplinary
/ Reproducibility of Results
/ Science
/ Science (multidisciplinary)
2023
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Evaluating the use of large language model in identifying top research questions in gastroenterology
by
Klang, Eyal
, Lahat, Adi
, Shatz, Zina
, Shachar, Eyal
, Avidan, Benjamin
, Glicksberg, Benjamin S.
in
631/114
/ 692/308
/ 692/4020
/ Artificial Intelligence
/ Endoscopy
/ Gastroenterologists
/ Gastroenterology
/ Humanities and Social Sciences
/ Humans
/ Inflammatory Bowel Diseases
/ Large language models
/ Microbiomes
/ multidisciplinary
/ Reproducibility of Results
/ Science
/ Science (multidisciplinary)
2023
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Evaluating the use of large language model in identifying top research questions in gastroenterology
by
Klang, Eyal
, Lahat, Adi
, Shatz, Zina
, Shachar, Eyal
, Avidan, Benjamin
, Glicksberg, Benjamin S.
in
631/114
/ 692/308
/ 692/4020
/ Artificial Intelligence
/ Endoscopy
/ Gastroenterologists
/ Gastroenterology
/ Humanities and Social Sciences
/ Humans
/ Inflammatory Bowel Diseases
/ Large language models
/ Microbiomes
/ multidisciplinary
/ Reproducibility of Results
/ Science
/ Science (multidisciplinary)
2023
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Evaluating the use of large language model in identifying top research questions in gastroenterology
Journal Article
Evaluating the use of large language model in identifying top research questions in gastroenterology
2023
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Overview
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.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
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