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Is ChatGPT accurate and reliable in answering questions regarding head and neck cancer?
- Source :
- Frontiers in Oncology; 2023, p1-7, 7p
- Publication Year :
- 2023
-
Abstract
- Background and objective: Chat Generative Pre-trained Transformer (ChatGPT) is an artificial intelligence (AI)-based language processing model using deep learning to create human-like text dialogue. It has been a popular source of information covering vast number of topics including medicine. Patient education in head and neck cancer (HNC) is crucial to enhance the understanding of patients about their medical condition, diagnosis, and treatment options. Therefore, this study aims to examine the accuracy and reliability of ChatGPT in answering questions regarding HNC. Methods: 154 head and neck cancer-related questions were compiled from sources including professional societies, institutions, patient support groups, and social media. These questions were categorized into topics like basic knowledge, diagnosis, treatment, recovery, operative risks, complications, follow-up, and cancer prevention. ChatGPT was queried with each question, and two experienced head and neck surgeons assessed each response independently for accuracy and reproducibility. Responses were rated on a scale: (1) comprehensive/correct, (2) incomplete/partially correct, (3) a mix of accurate and inaccurate/misleading, and (4) completely inaccurate/irrelevant. Discrepancies in grading were resolved by a third reviewer. Reproducibility was evaluated by repeating questions and analyzing grading consistency. Results: ChatGPT yielded “comprehensive/correct” responses to 133/154 (86.4%) of the questions whereas, rates of “incomplete/partially correct” and “mixed with accurate and inaccurate data/misleading” responses were 11% and 2.6%, respectively. There were no “completely inaccurate/irrelevant” responses. According to category, the model provided “comprehensive/correct” answers to 80.6% of questions regarding “basic knowledge”, 92.6% related to “diagnosis”, 88.9% related to “treatment”, 80% related to “recovery – operative risks – complications – follow-up”, 100% related to “cancer prevention” and 92.9% related to “other”. There was not any significant difference between the categories regarding the grades of ChatGPT responses (p=0.88). The rate of reproducibility was 94.1% (145 of 154 questions). Conclusion: ChatGPT generated substantially accurate and reproducible information to diverse medical queries related to HNC. Despite its limitations, Frontiers in Oncology 01 frontiersin.org OPEN ACCESS EDITED BY Peter Polverini, University of Michigan, United States REVIEWED BY Timothy Dean Malouff, University of Oklahoma, United States Leila Allahqoli, Iran University of Medical Sciences, Iran *CORRESPONDENCE A. Erim Pamuk ahmeterimpamuk@hacettepe.edu.tr RECEIVED 10 July 2023 ACCEPTED 13 November 2023 PUBLISHED 01 December 2023 CITATION Kus¸cu O, Pamuk AE, Sütay Süslü N and Hosal S (2023) Is ChatGPT accurate and reliable in answering questions regarding head and neck cancer? Front. Oncol. 13:1256459. doi: 10.3389/fonc.2023.1256459 COPYRIGHT © 2023 Kus¸cu, Pamuk, Sütay Süslü and Hosal. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE Original Research PUBLISHED 01 December 2023 DOI 10.3389/fonc.2023.1256459 it can be a useful source of information for both patients and medical professionals. With further developments in the model, ChatGPT can also play a crucial role in clinical decision support to provide the clinicians with up-todate information. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 2234943X
- Database :
- Complementary Index
- Journal :
- Frontiers in Oncology
- Publication Type :
- Academic Journal
- Accession number :
- 174280979
- Full Text :
- https://doi.org/10.3389/fonc.2023.1256459