Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment

Artificial intelligence chatbots and large language models in dental education: Worldwide survey of educators

INTRODUCTION

Interest is growing in the potential of artificial intelligence (AI) chatbots and large language models like OpenAI's ChatGPT and Google's Gemini, particularly in dental education. To explore dental educators' perceptions of AI chatbots and large language models, specifically their potential benefits and challenges for dental education.

MATERIALS AND METHODS

A global cross-sectional survey was conducted in May-June 2023 using a 31-item online-questionnaire to assess dental educators' perceptions of AI chatbots like ChatGPT and their influence on dental education. Dental educators, representing diverse backgrounds, were asked about their use of AI, its perceived impact, barriers to using chatbots, and the future role of AI in this field.

RESULTS

428 dental educators (survey views = 1516; response rate = 28%) with a median [25/75th percentiles] age of 45 [37, 56] and 16 [8, 25] years of experience participated, with the majority from the Americas (54%), followed by Europe (26%) and Asia (10%). Thirty-one percent of respondents already use AI tools, with 64% recognising their potential in dental education. Perception of AI's potential impact on dental education varied by region, with Africa (4[4-5]), Asia (4[4-5]), and the Americas (4[3-5]) perceiving more potential than Europe (3[3-4]). Educators stated that AI chatbots could enhance knowledge acquisition (74.3%), research (68.5%), and clinical decision-making (63.6%) but expressed concern about AI's potential to reduce human interaction (53.9%). Dental educators' chief concerns centred around the absence of clear guidelines and training for using AI chatbots.

CONCLUSION

A positive yet cautious view towards AI chatbot integration in dental curricula is prevalent, underscoring the need for clear implementation guidelines.

The Future of Orthodontics: Deep Learning Technologies

Deep learning has emerged as a revolutionary technical advancement in modern orthodontics, offering novel methods for diagnosis, treatment planning, and outcome prediction. Over the past 25 years, the field of dentistry has widely adopted information technology (IT), resulting in several benefits, including decreased expenses, increased efficiency, decreased need for human expertise, and reduced errors. The transition from preset rules to learning from real-world examples, particularly machine learning (ML) and artificial intelligence (AI), has greatly benefited the organization, analysis, and storage of medical data. Deep learning, a type of AI, enables robots to mimic human neural networks, allowing them to learn and make decisions independently without the need for explicit programming. Its ability to automate cephalometric analysis and enhance diagnosis through 3D imaging has revolutionized orthodontic operations. Deep learning models have the potential to significantly improve treatment outcomes and reduce human errors by accurately identifying anatomical characteristics on radiographs, thereby expediting analytical processes. Additionally, the use of 3D imaging technologies such as cone-beam computed tomography (CBCT) can facilitate precise treatment planning, allowing for comprehensive examinations of craniofacial architecture, tooth movements, and airway dimensions. In today's era of personalized medicine, deep learning's ability to customize treatments for individual patients has propelled the field of orthodontics forward tremendously. However, it is essential to address issues related to data privacy, model interpretability, and ethical considerations before orthodontic practices can use deep learning in an ethical and responsible manner. Modern orthodontics is evolving, thanks to the ability of deep learning to deliver more accurate, effective, and personalized orthodontic treatments, improving patient care as technology develops.

Examination of the reliability and readability of Chatbot Generative Pretrained Transformer's (ChatGPT) responses to questions about orthodontics and the evolution of these responses in an updated version

INTRODUCTION

This study aimed to assess the reliability and readability of Chatbot Generative Pretrained Transformer (ChatGPT) responses to questions about orthodontics and the evolution of these responses in an updated version.

METHODS

Frequently asked questions about orthodontics by laypeople on Web sites were determined using the Google Search Tool. These questions were asked to both ChatGPT's March 23 version and May 24 version on April 20, 2023, and July 12, 2023, respectively. Responses were assessed for readability and reliability using the Flesch-Kincaid and DISCERN tests.

RESULTS

The mean DISCERN value for general questions was 2.96 ± 0.05, 3.04 ± 0.06, 2.38 ± 0.27, and 2.82 ± 0.31 for treatment-related questions; the mean Flesch-Kincaid Reading Ease score for general questions was 29.28 ± 8.22, 25.12 ± 7.39, 47.67 ± 10.77, and 41.60 ± 9.54 for treatment-related questions; mean Flesch-Kincaid Grade Level for general questions was 14.52 ± 1.48 and 14.04 ± 1.25 and 11.90 ± 2.08 and 11.41 ± 1.88 for treatment-related questions; in first and second evaluations respectively (P = 0.001).

CONCLUSIONS

In the second evaluation, the reliability of the answers given to general questions and treatment-related questions increased. However, in both evaluations, the reliability of the answers was found to be moderate according to the DISCERN tool. On the second evaluation, Flesch Reading Ease Scores for both general questions and treatment-related questions decreased, meaning that the readability of the new response texts became more difficult. Flesch-Kincaid Grade Level results were found at the college graduate level in the first and second evaluations for general questions and at the high school level in the first and second evaluations for treatment-related questions.

Evaluating capabilities of large language models: Performance of GPT-4 on surgical knowledge assessments

BACKGROUND

Artificial intelligence has the potential to dramatically alter health care by enhancing how we diagnose and treat disease. One promising artificial intelligence model is ChatGPT, a general-purpose large language model trained by OpenAI. ChatGPT has shown human-level performance on several professional and academic benchmarks. We sought to evaluate its performance on surgical knowledge questions and assess the stability of this performance on repeat queries.

METHODS

We evaluated the performance of ChatGPT-4 on questions from the Surgical Council on Resident Education question bank and a second commonly used surgical knowledge assessment, referred to as Data-B. Questions were entered in 2 formats: open-ended and multiple-choice. ChatGPT outputs were assessed for accuracy and insights by surgeon evaluators. We categorized reasons for model errors and the stability of performance on repeat queries.

RESULTS

A total of 167 Surgical Council on Resident Education and 112 Data-B questions were presented to the ChatGPT interface. ChatGPT correctly answered 71.3% and 67.9% of multiple choice and 47.9% and 66.1% of open-ended questions for Surgical Council on Resident Education and Data-B, respectively. For both open-ended and multiple-choice questions, approximately two-thirds of ChatGPT responses contained nonobvious insights. Common reasons for incorrect responses included inaccurate information in a complex question (n = 16, 36.4%), inaccurate information in a fact-based question (n = 11, 25.0%), and accurate information with circumstantial discrepancy (n = 6, 13.6%). Upon repeat query, the answer selected by ChatGPT varied for 36.4% of questions answered incorrectly on the first query; the response accuracy changed for 6/16 (37.5%) questions.

CONCLUSION

Consistent with findings in other academic and professional domains, we demonstrate near or above human-level performance of ChatGPT on surgical knowledge questions from 2 widely used question banks. ChatGPT performed better on multiple-choice than open-ended questions, prompting questions regarding its potential for clinical application. Unique to this study, we demonstrate inconsistency in ChatGPT responses on repeat queries. This finding warrants future consideration including efforts at training large language models to provide the safe and consistent responses required for clinical application. Despite near or above human-level performance on question banks and given these observations, it is unclear whether large language models such as ChatGPT are able to safely assist clinicians in providing care.

The efficacy of artificial intelligence in urology: a detailed analysis of kidney stone-related queries

PURPOSE

The study aimed to assess the efficacy of OpenAI's advanced AI model, ChatGPT, in diagnosing urological conditions, focusing on kidney stones.

MATERIALS AND METHODS

A set of 90 structured questions, compliant with EAU Guidelines 2023, was curated by seasoned urologists for this investigation. We evaluated ChatGPT's performance based on the accuracy and completeness of its responses to two types of questions [binary (true/false) and descriptive (multiple-choice)], stratified into difficulty levels: easy, moderate, and complex. Furthermore, we analyzed the model's learning and adaptability capacity by reassessing the initially incorrect responses after a 2 week interval.

RESULTS

The model demonstrated commendable accuracy, correctly answering 80% of binary questions (n:45) and 93.3% of descriptive questions (n:45). The model's performance showed no significant variation across different question difficulty levels, with p-values of 0.548 for accuracy and 0.417 for completeness, respectively. Upon reassessment of initially 12 incorrect responses (9 binary to 3 descriptive) after two weeks, ChatGPT's accuracy showed substantial improvement. The mean accuracy score significantly increased from 1.58 ± 0.51 to 2.83 ± 0.93 (p = 0.004), underlining the model's ability to learn and adapt over time.

CONCLUSION

These findings highlight the potential of ChatGPT in urological diagnostics, but also underscore areas requiring enhancement, especially in the completeness of responses to complex queries. The study endorses AI's incorporation into healthcare, while advocating for prudence and professional supervision in its application.

ChatGPT in healthcare: A taxonomy and systematic review

The recent release of ChatGPT, a chat bot research project/product of natural language processing (NLP) by OpenAI, stirs up a sensation among both the general public and medical professionals, amassing a phenomenally large user base in a short time. This is a typical example of the 'productization' of cutting-edge technologies, which allows the general public without a technical background to gain firsthand experience in artificial intelligence (AI), similar to the AI hype created by AlphaGo (DeepMind Technologies, UK) and self-driving cars (Google, Tesla, etc.). However, it is crucial, especially for healthcare researchers, to remain prudent amidst the hype. This work provides a systematic review of existing publications on the use of ChatGPT in healthcare, elucidating the 'status quo' of ChatGPT in medical applications, for general readers, healthcare professionals as well as NLP scientists. The large biomedical literature database PubMed is used to retrieve published works on this topic using the keyword 'ChatGPT'. An inclusion criterion and a taxonomy are further proposed to filter the search results and categorize the selected publications, respectively. It is found through the review that the current release of ChatGPT has achieved only moderate or 'passing' performance in a variety of tests, and is unreliable for actual clinical deployment, since it is not intended for clinical applications by design. We conclude that specialized NLP models trained on (bio)medical datasets still represent the right direction to pursue for critical clinical applications.

Large Language Models and Artificial Intelligence: A Primer for Plastic Surgeons on the Demonstrated and Potential Applications, Promises, and Limitations of ChatGPT

BACKGROUND

The rapidly evolving field of artificial intelligence (AI) holds great potential for plastic surgeons. ChatGPT, a recently released AI large language model (LLM), promises applications across many disciplines, including healthcare.

OBJECTIVES

The aim of this article was to provide a primer for plastic surgeons on AI, LLM, and ChatGPT, including an analysis of current demonstrated and proposed clinical applications.

METHODS

A systematic review was performed identifying medical and surgical literature on ChatGPT's proposed clinical applications. Variables assessed included applications investigated, command tasks provided, user input information, AI-emulated human skills, output validation, and reported limitations.

RESULTS

The analysis included 175 articles reporting on 13 plastic surgery applications and 116 additional clinical applications, categorized by field and purpose. Thirty-four applications within plastic surgery are thus proposed, with relevance to different target audiences, including attending plastic surgeons (n = 17, 50%), trainees/educators (n = 8, 24.0%), researchers/scholars (n = 7, 21%), and patients (n = 2, 6%). The 15 identified limitations of ChatGPT were categorized by training data, algorithm, and ethical considerations.

CONCLUSIONS

Widespread use of ChatGPT in plastic surgery will depend on rigorous research of proposed applications to validate performance and address limitations. This systemic review aims to guide research, development, and regulation to safely adopt AI in plastic surgery.

Accuracy and Completeness of ChatGPT-Generated Information on Interceptive Orthodontics: A Multicenter Collaborative Study

Background: this study aims to investigate the accuracy and completeness of ChatGPT in answering questions and solving clinical scenarios of interceptive orthodontics. Materials and Methods: ten specialized orthodontists from ten Italian postgraduate orthodontics schools developed 21 clinical open-ended questions encompassing all of the subspecialities of interceptive orthodontics and 7 comprehensive clinical cases. Questions and scenarios were inputted into ChatGPT4, and the resulting answers were evaluated by the researchers using predefined accuracy (range 1-6) and completeness (range 1-3) Likert scales. Results: For the open-ended questions, the overall median score was 4.9/6 for the accuracy and 2.4/3 for completeness. In addition, the reviewers rated the accuracy of open-ended answers as entirely correct (score 6 on Likert scale) in 40.5% of cases and completeness as entirely correct (score 3 n Likert scale) in 50.5% of cases. As for the clinical cases, the overall median score was 4.9/6 for accuracy and 2.5/3 for completeness. Overall, the reviewers rated the accuracy of clinical case answers as entirely correct in 46% of cases and the completeness of clinical case answers as entirely correct in 54.3% of cases. Conclusions: The results showed a high level of accuracy and completeness in AI responses and a great ability to solve difficult clinical cases, but the answers were not 100% accurate and complete. ChatGPT is not yet sophisticated enough to replace the intellectual work of human beings.

ChatGPT to Enhance Learning in Dental Education at a Historically Black Medical College

The recent rise of powerful large language model (LLM)-based AI tools, exemplified by ChatGPT and Bard, poses a great challenge to contemporary dental education. It simultaneously offers a unique resource that potentially complements today's teaching and learning, where existing widely available learning resources have often fallen short. Although the LLM tools will shape both the clinical and educational aspects of dentistry profoundly, the didactic curricula, which primarily rely on lecture-based courses where instructors impart knowledge through presentations and discussions, need to be upgraded urgently. In this paper, we used dental course materials, syllabi, and textbooks adopted currently in the School of Dentistry (SOD) at Meharry Medical College to assess the potential utility and effectiveness of ChatGPT in dental education. We collected the responses of the chatbot to questions as well as students' interactions with it for assessment. Our results showed that ChatGPT can assist in dental essay writing and generate relevant content for dental students, in addition to other benefits. The limitations of ChatGPT were also discussed in the paper.

AI in Orthodontics: Revolutionizing Diagnostics and Treatment Planning-A Comprehensive Review

The advent of artificial intelligence (AI) in medicine has transformed various medical specialties, including orthodontics. AI has shown promising results in enhancing the accuracy of diagnoses, treatment planning, and predicting treatment outcomes. Its usage in orthodontic practices worldwide has increased with the availability of various AI applications and tools. This review explores the principles of AI, its applications in orthodontics, and its implementation in clinical practice. A comprehensive literature review was conducted, focusing on AI applications in dental diagnostics, cephalometric evaluation, skeletal age determination, temporomandibular joint (TMJ) evaluation, decision making, and patient telemonitoring. Due to study heterogeneity, no meta-analysis was possible. AI has demonstrated high efficacy in all these areas, but variations in performance and the need for manual supervision suggest caution in clinical settings. The complexity and unpredictability of AI algorithms call for cautious implementation and regular manual validation. Continuous AI learning, proper governance, and addressing privacy and ethical concerns are crucial for successful integration into orthodontic practice.

ChatGPT to enhance learning in dental education at a historically black medical college

The recent rise of powerful large language model (LLM)-based AI tools, exemplified by ChatGPT and Bard, poses a great challenge to contemporary dental education while simultaneously offering a unique resource and approach that potentially complements today's teaching and learning, where existing widely available learning resources have often fallen short. Although both the clinical and educational aspects of dentistry will be shaped profoundly by the LLM tools, the didactic curricula, which primarily rely on lecture-based courses where instructors impart knowledge through presentations and discussions, need to be upgraded urgently. In this paper, we used dental course materials, syllabi, and textbooks adopted currently in the School of Dentistry (SOD) at Meharry Medical College to assess the potential utility and effectiveness of ChatGPT in dental education. We collected the responses of the chatbot to questions as well as students' interactions with it for assessment. Our results showed that ChatGPT can assist in dental essay writing and generate relevant content for dental students, in addition to other benefits. The limitations of ChatGPT were also discussed in the paper.

ChatGPT to enhance learning in dental education at a historically black medical college

The recent rise of powerful large language model (LLM)-based AI tools, exemplified by ChatGPT and Bard, poses a great challenge to contemporary dental education while simultaneously offering a unique resource and approach that potentially complements today's teaching and learning, where existing widely available learning resources have often fallen short. Although both the clinical and educational aspects of dentistry will be shaped profoundly by the LLM tools, the didactic curricula, which primarily rely on lecture-based courses where instructors impart knowledge through presentations and discussions, need to be upgraded urgently. In this paper, we used dental course materials, syllabi, and textbooks adopted currently in the School of Dentistry (SOD) at Meharry Medical College to assess the potential utility and effectiveness of ChatGPT in dental education. We collected the responses of the chatbot to questions as well as students' interactions with it for assessment. Our results showed that ChatGPT can assist in dental essay writing and generate relevant content for dental students, in addition to other benefits. The limitations of ChatGPT were also discussed in the paper.

BIR: Biomedical Information Retrieval System for Cancer Treatment in Electronic Health Record Using Transformers

The rapid growth of electronic health records (EHRs) has led to unprecedented biomedical data. Clinician access to the latest patient information can improve the quality of healthcare. However, clinicians have difficulty finding information quickly and easily due to the sheer data mining volume. Biomedical information retrieval (BIR) systems can help clinicians find the information required by automatically searching EHRs and returning relevant results. However, traditional BIR systems cannot understand the complex relationships between EHR entities. Transformers are a new type of neural network that is very effective for natural language processing (NLP) tasks. As a result, transformers are well suited for tasks such as machine translation and text summarization. In this paper, we propose a new BIR system for EHRs that uses transformers for predicting cancer treatment from EHR. Our system can understand the complex relationships between the different entities in an EHR, which allows it to return more relevant results to clinicians. We evaluated our system on a dataset of EHRs and found that it outperformed state-of-the-art BIR systems on various tasks, including medical question answering and information extraction. Our results show that Transformers are a promising approach for BIR in EHRs, reaching an accuracy and an F1-score of 86.46%, and 0.8157, respectively. We believe that our system can help clinicians find the information they need more quickly and easily, leading to improved patient care.

The Evolution of Robin Sequence Treatment Based on the Biomimetic Interdisciplinary Approach: A Historical Review

The Robin sequence is a congenital anomaly characterized by a triad of features: micrognathia, glossoptosis, and airway obstruction. This comprehensive historical review maps the evolution of approaches and appliances for its treatment from the past to the current modern possibilities of an interdisciplinary combination of modern engineering, medicine, materials, and computer science combined approach with emphasis on designing appliances inspired by nature and individual human anatomy. Current biomimetic designs are clinically applied, resulting in appliances that are more efficient, comfortable, sustainable, and safer than legacy traditional designs. This review maps the treatment modalities that have been used for patients with a Robin sequence over the years. Early management of the Robin sequence focused primarily on airway maintenance and feeding support, while current management strategies involve both nonsurgical and surgical interventions and biomimetic biocompatible personalized appliances. The goal of this paper was to provide a review of the evolution of management strategies for patients with the Robin sequence that led to the current interdisciplinary biomimetic approaches impacting the future of Robin Sequence treatment with biomimetics at the forefront.

Should ChatGPT Have Some Applicability in the Management of Emergency Dental Care for Emigrant Adults and Children?

How to cite this article: Veseli E, Tovani-Palone MR, Veseli A, et al. Should ChatGPT Have Some Applicability in the Management of Emergency Dental Care for Emigrant Adults and Children? J Contemp Dent Pract 2023;24(11):819-820. Keywords: Artificial intelligence, Dental care, Dentistry, Emigrants and immigrants, Public health.

Smartphone Applications in Dentistry: A Scoping Review

This scoping review aims to investigate the latest literature concerning the use of smartphone applications (apps) in the prevention, management, and monitoring of oral diseases. Smartphone applications are software programs that are designed to run on smartphones. Nowadays, smartphones are regularly used by people of all ages, and mobile health apps (MHAs) represent an important means of spreading information related to oral health, which is the state of the mouth and teeth, including the gums and other tissues. Several apps have been designed to promote prevention, diagnosis, and therapeutic adherence monitoring. This scoping review considered randomized clinical trials, cross-sectional studies, before-after (pre-post) studies with no control group, and observational studies. Once the inclusion and exclusion criteria had been defined, a preliminary confined search was performed on PubMed and Scopus; key terms from the collected articles were selected to design a search strategy, and then a search of all the included articles' reference lists was run for further research. Studies were excluded if they did not fulfill the inclusion criteria. The preferred reporting items for scoping reviews (PRISMA-ScR) consensus was followed. The risk of bias was evaluated by providing a qualitative analysis of the clinical studies via the National Heart, Lung, and Blood Institute (NHLBI) Quality Assessment of Controlled Intervention Studies, Observational Cohort Studies, and Cross-Sectional Studies (NHLBI, NIH). A total of 21 studies were included in this review. As it is clear from the studies selected, the literature indicates that MHAs are effective in improving oral hygiene in adolescents and children and reducing the dental plaque index, including in patients undergoing orthodontic treatment. MHAs are also able to reduce the symptoms of patients affected by obstructive sleep apnea-hypopnea syndrome (OSAHS) and improve the swallowing-related quality of life of elderly patients. MHAs are furthermore recommended to decrease dental anxiety among patients, both during dental procedures and the post-operative period. MHAs are useful to spread knowledge about traumatic dental injuries among non-oral health professionals and to monitor dental erosion and awake bruxism. MHAs' clinical outcomes might have been influenced by the demographic features of the subjects involved. Further studies considering a longer follow-up period and larger samples are needed. In conclusion, MHAs can be considered a useful tool to monitor oral disease and increase patients' quality of life related to oral health.

Application of Artificial Intelligence in Orthodontics: Current State and Future Perspectives

In recent years, there has been the notable emergency of artificial intelligence (AI) as a transformative force in multiple domains, including orthodontics. This review aims to provide a comprehensive overview of the present state of AI applications in orthodontics, which can be categorized into the following domains: (1) diagnosis, including cephalometric analysis, dental analysis, facial analysis, skeletal-maturation-stage determination and upper-airway obstruction assessment; (2) treatment planning, including decision making for extractions and orthognathic surgery, and treatment outcome prediction; and (3) clinical practice, including practice guidance, remote care, and clinical documentation. We have witnessed a broadening of the application of AI in orthodontics, accompanied by advancements in its performance. Additionally, this review outlines the existing limitations within the field and offers future perspectives.

What is the current state of artificial intelligence applications in dentistry and orthodontics?

BACKGROUND

The use of Artificial Intelligence (AI) in the medical field has the potential to bring about significant improvements in patient care and outcomes. AI is being used in dentistry and more specifically in orthodontics through the development of diagnostic imaging tools, the development of treatment planning tools, and the development of robotic surgery. The aim of this study is to present the latest emerging AI softwares and applications in dental field to benefit from.

TYPES OF STUDIES REVIEWED

Search strategies were conducted in three electronic databases, with no date limits in the following databases up to April 30, 2023: MEDLINE, PUBMED, and GOOGLE® SCHOLAR for articles related to AI in dentistry & orthodontics. No inclusion and exclusion criteria were used for the selection of the articles. Most of the articles included (n = 79) are reviews of the literature, retro/prospective studies, systematic reviews and meta-analyses, and observational studies.

RESULTS

The use of AI in dentistry and orthodontics is a rapidly growing area of research and development, with the potential to revolutionize the field and bring about significant improvements in patient care and outcomes; this can save clinicians' chair-time and push for more individualized treatment plans. Results from the various studies reported in this review are suggestive that the accuracy of AI-based systems is quite promising and reliable.

PRACTICAL IMPLICATIONS

AI application in the healthcare field has proven to be efficient and helpful for the dentist to be more precise in diagnosis and clinical decision-making. These systems can simplify the tasks and provide results in quick time which can save dentists time and help them perform their duties more efficiently. These systems can be of greater aid and can be used as auxiliary support for dentists with lesser experience.

Bridging the Gap: Exploring Opportunities, Challenges, and Problems in Integrating Assistive Technologies, Robotics, and Automated Machines into the Health Domain

The field of healthcare is continually evolving and advancing due to new technologies and innovations [...].

Universal skepticism of ChatGPT: a review of early literature on chat generative pre-trained transformer

ChatGPT, a new language model developed by OpenAI, has garnered significant attention in various fields since its release. This literature review provides an overview of early ChatGPT literature across multiple disciplines, exploring its applications, limitations, and ethical considerations. The review encompasses Scopus-indexed publications from November 2022 to April 2023 and includes 156 articles related to ChatGPT. The findings reveal a predominance of negative sentiment across disciplines, though subject-specific attitudes must be considered. The review highlights the implications of ChatGPT in many fields including healthcare, raising concerns about employment opportunities and ethical considerations. While ChatGPT holds promise for improved communication, further research is needed to address its capabilities and limitations. This literature review provides insights into early research on ChatGPT, informing future investigations and practical applications of chatbot technology, as well as development and usage of generative AI.

Evaluating Capabilities of Large Language Models: Performance of GPT4 on Surgical Knowledge Assessments

Background

Artificial intelligence (AI) has the potential to dramatically alter healthcare by enhancing how we diagnosis and treat disease. One promising AI model is ChatGPT, a large general-purpose language model trained by OpenAI. The chat interface has shown robust, human-level performance on several professional and academic benchmarks. We sought to probe its performance and stability over time on surgical case questions.

Methods

We evaluated the performance of ChatGPT-4 on two surgical knowledge assessments: the Surgical Council on Resident Education (SCORE) and a second commonly used knowledge assessment, referred to as Data-B. Questions were entered in two formats: open-ended and multiple choice. ChatGPT output were assessed for accuracy and insights by surgeon evaluators. We categorized reasons for model errors and the stability of performance on repeat encounters.

Results

A total of 167 SCORE and 112 Data-B questions were presented to the ChatGPT interface. ChatGPT correctly answered 71% and 68% of multiple-choice SCORE and Data-B questions, respectively. For both open-ended and multiple-choice questions, approximately two-thirds of ChatGPT responses contained non-obvious insights. Common reasons for inaccurate responses included: inaccurate information in a complex question (n=16, 36.4%); inaccurate information in fact-based question (n=11, 25.0%); and accurate information with circumstantial discrepancy (n=6, 13.6%). Upon repeat query, the answer selected by ChatGPT varied for 36.4% of inaccurate questions; the response accuracy changed for 6/16 questions.

Conclusion

Consistent with prior findings, we demonstrate robust near or above human-level performance of ChatGPT within the surgical domain. Unique to this study, we demonstrate a substantial inconsistency in ChatGPT responses with repeat query. This finding warrants future consideration and presents an opportunity to further train these models to provide safe and consistent responses. Without mental and/or conceptual models, it is unclear whether language models such as ChatGPT would be able to safely assist clinicians in providing care.

ChatGPT for Future Medical and Dental Research

ChatGPT is an artificial intelligence (AI) chatbot developed by OpenAI and it first became available to the public in November 2022. ChatGPT can assist in finding academic papers on the web and summarizing them. This chatbot has the potential to be applied in scientific writing, it has the ability to generate automated drafts, summarize articles, and translate content from several languages. This in turn can make academic writing faster and less challenging. However, due to ethical considerations, its use in scientific writing should be regulated and carefully monitored. Few papers have discussed the use of ChatGPT in scientific research writing. This review aims to discuss all the relevant published papers that discuss the use of ChatGPT in medical and dental research.

ChatGPT in Dentistry: A Comprehensive Review

Chat generative pre-trained transformer (ChatGPT) is an artificial intelligence chatbot that uses natural language processing that can respond to human input in a conversational manner. ChatGPT has numerous applications in the health care system including dentistry; it is used in diagnoses and for assessing disease risk and scheduling appointments. It also has a role in scientific research. In the dental field, it has provided many benefits such as detecting dental and maxillofacial abnormalities on panoramic radiographs and identifying different dental restorations. Therefore, it helps in decreasing the workload. But even with these benefits, one should take into consideration the risks and limitations of this chatbot. Few articles mentioned the use of ChatGPT in dentistry. This comprehensive review represents data collected from 66 relevant articles using PubMed and Google Scholar as databases. This review aims to discuss all relevant published articles on the use of ChatGPT in dentistry.