Review began 06/13/2023 Review ended 07/17/2023 Published 07/19/2023 © Copyright 2023 Mago et al. This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The Potential Usefulness of ChatGPT in Oral and Maxillofacial Radiology Jyoti Mago , Manoj Sharma 1. Oral and Maxillofacial Radiology, University of Nevada, Las Vegas (UNLV), Las Vegas, USA 2. Public Health, University of Nevada, Las Vegas (UNLV), Las Vegas, USA Corresponding author: Jyoti Mago, jyoti.mago@unlv.edu Abstract Aim This study aimed to evaluate the potential usefulness of Chat Generated Pre-Trained Transformer-3 (ChatGPT-3) in oral and maxillofacial radiology for report writing by identifying radiographic anatomical landmarks and learning about oral and maxillofacial pathologies and their radiographic features. The study also aimed to evaluate the performance of ChatGPT-3 and its usage in oral and maxillofacial radiology training. Materials and methods A questionnaire consisting of 80 questions was queried on the OpenAI app ChatGPT-3. The questions were stratified based on three categories. The categorization was based on random anatomical landmarks, oral and maxillofacial pathologies, and the radiographic features of some of these pathologies. One oral and maxillofacial radiologist evaluated queries that were answered by the ChatGPT-3 model and rated them on a 4-point, modified Likert scale. The post-survey analysis for the performance of ChatGPT-3 was based on the Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis, its application in oral and maxillofacial radiology training, and its recommended use. Results In order of efficiency, Chat GPT-3 gave 100% accuracy in describing radiographic landmarks. However, the content of the oral and maxillofacial pathologies was limited to major or characteristic radiographic features. The mean scores for the queries related to the anatomic landmarks, oral and maxillofacial pathologies, and radiographic features of the oral and maxillofacial pathologies were 3.94, 3.85, and 3.96, respectively. However, the median and mode scores were 4 and were similar to all categories. The data for the oral and maxillofacial pathologies when the questions were not specifically included in the format of the introduction of the pathology, causes, symptoms, and treatment. Out of two abbreviations, one was not answered correctly. Conclusion The study showed that ChatGPT-3 is efficient in describing the pathology, characteristic radiographic features, and describing anatomical landmarks. ChatGPT-3 can be used as an adjunct when an oral radiologist needs additional information on any pathology, however, it cannot be the mainstay for reference. ChatGPT-3 is less detail-oriented, and the data has a risk of infodemics and the possibility of medical errors. However, Chat GPT-3 can be an excellent tool in helping the community in increasing the knowledge and awareness of various pathologies and decreasing the anxiety of the patients while dental healthcare professionals formulate an appropriate treatment plan. Categories: Radiology, Other, Dentistry Keywords: radiographic features, pathology, oral and maxillofacial radiology, chatgpt, open-ai Introduction With the advent of technology, artificial intelligence is emerging to be and is currently among the most researched technologies. Alan Turing, in 1950, suggested the Turing test, which is a test to compare if a machine can accomplish intelligence at the human level [1]. Five years later, in 1955, the terminology AI was first suggested in a two-month workshop led by McCarthy J et al. [2]. Machine learning (ML) algorithms; and evidence-based dentistry both aim at analyzing the current advancements in healthcare and precision medicine to minimize human error [3]. Compared to evidence-based dentistry, machine learning can achieve its aims faster due to the method of how the data are collected [3]. However, machine learning requires a lot of data collection, which may be biased [3]. Chat Generated Pre-Trained Transformer-3 (ChatGPT-3) is an OpenAI model and a powerful member of 1 2 Open Access Original Article DOI: 10.7759/cureus.42133 How to cite this article Mago J, Sharma M (July 19, 2023) The Potential Usefulness of ChatGPT in Oral and Maxillofacial Radiology. Cureus 15(7): e42133. DOI 10.7759/cureus.42133