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

被引:56
作者
Lahat, Adi [1 ]
Shachar, Eyal [1 ]
Avidan, Benjamin [1 ]
Shatz, Zina [1 ]
Glicksberg, Benjamin S. [2 ]
Klang, Eyal [3 ]
机构
[1] Tel Aviv Univ, Chaim Sheba Med Ctr, Dept Gastroenterol, Tel Aviv, Israel
[2] Icahn Sch Med Mt Sinai, Hasso Plattner Inst Digital Hlth, New York, NY USA
[3] Tel Aviv Univ, ARC Innovat Ctr, Chaim Sheba Med Ctr, Sami Sagol AI Hub, Tel Aviv, Israel
关键词
D O I
10.1038/s41598-023-31412-2
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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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页数:6
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