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The role of ChatGPT in enhancing ENT surgical training – a trainees’ perspective

Published online by Cambridge University Press:  16 August 2023

Laura Brennan*
Affiliation:
Department of ENT, St Michaels Hospital, University Hospitals Bristol and Weston, Bristol, UK
Ramkishan Balakumar
Affiliation:
Department of ENT, St Michaels Hospital, University Hospitals Bristol and Weston, Bristol, UK
Warren Bennett
Affiliation:
Department of ENT, St Michaels Hospital, University Hospitals Bristol and Weston, Bristol, UK
*
Corresponding author: Laura Brennan; Email: l.j.brennan94@gmail.com
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Abstract

Objective

ChatGPT, developed by Open AI (November 2022) is a powerful artificial intelligence language model, designed to produce human-like text from user-written prompts. Prompts must give context-specific information to produce valuable responses. Otolaryngology is a specialist field that sees limited exposure during undergraduate and postgraduate education. Additionally, otolaryngology trainees have seen a reduction in learning opportunities since the coronavirus disease 2019 pandemic.

Method

This article aims to give guidance on optimising the ChatGPT system in the context of education for otolaryngology by reviewing barriers to otolaryngology education and suggesting ways that ChatGPT can overcome them by providing examples using the authors’ experience.

Results

Overall, the authors saw that ChatGPT demonstrated some useful qualities, particularly with regards to assistance with communication skills and individualised patient responses.

Conclusion

Although ChatGPT cannot replace traditional mentorship and practical surgical experience, it can serve as an invaluable supplementary resource to education in otolaryngology.

Information

Type
Main Article
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press on behalf of J.L.O. (1984) LIMITED
Figure 0

Figure 1. (a) Snapshot of example response generated for key steps in tonsillectomy. Figure from chat.openAI.com. (b) Snapshot of example response generated for altered prompt for key steps in tonsillectomy. Figure from chat.openAI.com

Figure 1

Figure 2. Example response generated when chatbot notified of error. Figure from chat.openAI.com.

Figure 2

Figure 3. Example response generated when user inputted incorrect answer to revision question. Figure from chat.openAI.com. CN = cranial nerve.

Figure 3

Figure 4. Figure example response generated where chatbot establishes users’ needs. Figure from chat.openAI.com.

Figure 4

Figure 5. Example response generated from chatbot responding as a patient. Figure from chat.openAI.com.

Figure 5

Table 1. Author experiences of responses generated