Evidence-based potential of generative artificial intelligence large language models in orthodontics: a comparative study of ChatGPT, Google Bard, and Microsoft Bing.

BACKGROUND: The increasing utilization of large language models (LLMs) in Generative Artificial Intelligence across various medical and dental fields, and specifically orthodontics, raises questions about their accuracy. OBJECTIVE: This study aimed to assess and compare the answers offered by four LLMs: Google's Bard, OpenAI's ChatGPT-3.5, and ChatGPT-4, and Microsoft's Bing, in response to clinically relevant questions within the field of orthodontics. MATERIALS AND METHODS: Ten open-type clinical orthodontics-related questions were posed to the LLMs. The responses provided by the LLMs were assessed on a scale ranging from 0 (minimum) to 10 (maximum) points, benchmarked against robust scientific evidence, including consensus statements and systematic reviews, using a predefined rubric. After a 4-week interval from the initial evaluation, the answers were reevaluated to gauge intra-evaluator reliability. Statistical comparisons were conducted on the scores using Friedman's and Wilcoxon's tests to identify the model providing the answers with the most comprehensiveness, scientific accuracy, clarity, and relevance. RESULTS: Overall, no statistically significant differences between the scores given by the two evaluators, on both scoring occasions, were detected, so an average score for every LLM was computed. The LLM answers scoring the highest, were those of Microsoft Bing Chat (average score = 7.1), followed by ChatGPT 4 (average score = 4.7), Google Bard (average score = 4.6), and finally ChatGPT 3.5 (average score 3.8). While Microsoft Bing Chat statistically outperformed ChatGPT-3.5 (P-value = 0.017) and Google Bard (P-value = 0.029), as well, and Chat GPT-4 outperformed Chat GPT-3.5 (P-value = 0.011), all models occasionally produced answers with a lack of comprehensiveness, scientific accuracy, clarity, and relevance. LIMITATIONS: The questions asked were indicative and did not cover the entire field of orthodontics. CONCLUSIONS: Language models (LLMs) show great potential in supporting evidence-based orthodontics. However, their current limitations pose a potential risk of making incorrect healthcare decisions if utilized without careful consideration. Consequently, these tools cannot serve as a substitute for the orthodontist's essential critical thinking and comprehensive subject knowledge. For effective integration into practice, further research, clinical validation, and enhancements to the models are essential. Clinicians must be mindful of the limitations of LLMs, as their imprudent utilization could have adverse effects on patient care.

Evaluation of ChatGPT's Real-Life Implementation in Undergraduate Dental Education: Mixed Methods Study.

BACKGROUND: The recent artificial intelligence tool ChatGPT seems to offer a range of benefits in academic education while also raising concerns. Relevant literature encompasses issues of plagiarism and academic dishonesty, as well as pedagogy and educational affordances; yet, no real-life implementation of ChatGPT in the educational process has been reported to our knowledge so far. OBJECTIVE: This mixed methods study aimed to evaluate the implementation of ChatGPT in the educational process, both quantitatively and qualitatively. METHODS: In March 2023, a total of 77 second-year dental students of the European University Cyprus were divided into 2 groups and asked to compose a learning assignment on "Radiation Biology and Radiation Protection in the Dental Office," working collaboratively in small subgroups, as part of the educational semester program of the Dentomaxillofacial Radiology module. Careful planning ensured a seamless integration of ChatGPT, addressing potential challenges. One group searched the internet for scientific resources to perform the task and the other group used ChatGPT for this purpose. Both groups developed a PowerPoint (Microsoft Corp) presentation based on their research and presented it in class. The ChatGPT group students additionally registered all interactions with the language model during the prompting process and evaluated the final outcome; they also answered an open-ended evaluation questionnaire, including questions on their learning experience. Finally, all students undertook a knowledge examination on the topic, and the grades between the 2 groups were compared statistically, whereas the free-text comments of the questionnaires were thematically analyzed. RESULTS: Out of the 77 students, 39 were assigned to the ChatGPT group and 38 to the literature research group. Seventy students undertook the multiple choice question knowledge examination, and examination grades ranged from 5 to 10 on the 0-10 grading scale. The Mann-Whitney U test showed that students of the ChatGPT group performed significantly better (P=.045) than students of the literature research group. The evaluation questionnaires revealed the benefits (human-like interface, immediate response, and wide knowledge base), the limitations (need for rephrasing the prompts to get a relevant answer, general content, false citations, and incapability to provide images or videos), and the prospects (in education, clinical practice, continuing education, and research) of ChatGPT. CONCLUSIONS: Students using ChatGPT for their learning assignments performed significantly better in the knowledge examination than their fellow students who used the literature research methodology. Students adapted quickly to the technological environment of the language model, recognized its opportunities and limitations, and used it creatively and efficiently. Implications for practice: the study underscores the adaptability of students to technological innovations including ChatGPT and its potential to enhance educational outcomes. Educators should consider integrating ChatGPT into curriculum design; awareness programs are warranted to educate both students and educators about the limitations of ChatGPT, encouraging critical engagement and responsible use.

Evaluation of the Performance of Generative AI Large Language Models ChatGPT, Google Bard, and Microsoft Bing Chat in Supporting Evidence-Based Dentistry: Comparative Mixed Methods Study.

BACKGROUND: The increasing application of generative artificial intelligence large language models (LLMs) in various fields, including dentistry, raises questions about their accuracy. OBJECTIVE: This study aims to comparatively evaluate the answers provided by 4 LLMs, namely Bard (Google LLC), ChatGPT-3.5 and ChatGPT-4 (OpenAI), and Bing Chat (Microsoft Corp), to clinically relevant questions from the field of dentistry. METHODS: The LLMs were queried with 20 open-type, clinical dentistry-related questions from different disciplines, developed by the respective faculty of the School of Dentistry, European University Cyprus. The LLMs' answers were graded 0 (minimum) to 10 (maximum) points against strong, traditionally collected scientific evidence, such as guidelines and consensus statements, using a rubric, as if they were examination questions posed to students, by 2 experienced faculty members. The scores were statistically compared to identify the best-performing model using the Friedman and Wilcoxon tests. Moreover, the evaluators were asked to provide a qualitative evaluation of the comprehensiveness, scientific accuracy, clarity, and relevance of the LLMs' answers. RESULTS: Overall, no statistically significant difference was detected between the scores given by the 2 evaluators; therefore, an average score was computed for every LLM. Although ChatGPT-4 statistically outperformed ChatGPT-3.5 (P=.008), Bing Chat (P=.049), and Bard (P=.045), all models occasionally exhibited inaccuracies, generality, outdated content, and a lack of source references. The evaluators noted instances where the LLMs delivered irrelevant information, vague answers, or information that was not fully accurate. CONCLUSIONS: This study demonstrates that although LLMs hold promising potential as an aid in the implementation of evidence-based dentistry, their current limitations can lead to potentially harmful health care decisions if not used judiciously. Therefore, these tools should not replace the dentist's critical thinking and in-depth understanding of the subject matter. Further research, clinical validation, and model improvements are necessary for these tools to be fully integrated into dental practice. Dental practitioners must be aware of the limitations of LLMs, as their imprudent use could potentially impact patient care. Regulatory measures should be established to oversee the use of these evolving technologies.

Taurodontism in simultaneous existence with multiple supernumerary teeth: A case report.

Supernumerary teeth and taurodontism are both common dental anomalies when found as isolated entities. However, simultaneous presence in the same individual without a syndrome is rarely reported in the literature. This case report describes a 20-year-old non-syndromic male with multiple supernumerary teeth in association with multiple molar and premolar taurodonts and no family history of genetic predisposing factors. Taurodontism was measured and confirmed through cone-beam computed tomography for accuracy of the classification. Early diagnosis with the aid of radiographic imaging and persistent follow-up are crucial to treatment.

Dental students' and faculty perception of online exams with e-invigilation in Cyprus.

INTRODUCTION: During the recent pandemic, e-learning and e-assessment methods have been implemented worldwide, providing opportunities for further implementation in the dental curriculum. This study aims to research the dental students' and dental faculty's perceptions of online exams with e-invigilation. MATERIALS AND METHODS: Online questionnaires were developed and delivered, after three semesters of online exams, to all students and faculty. Descriptive statistics were performed, and answers were grouped into Principal Components (PC) using Principal Component Analysis (PCA). Statistical significance was set at p < .05. RESULTS: Two-hundred and sixty dental students (83.7%) and 24 dental faculty members (63.1%) answered the online questionnaires. PCA of students' responses revealed 4 PC, 'University support to students', 'Comparison between online and face-to-face exams', 'Preparation for the online exams' and 'Attitudes towards the technology used for the online exams'. PCA of faculty responses revealed 5 PC: 'Comparison between online and face-to-face exams', 'University support to faculty', 'Faculty attitudes towards the exam procedures', 'Human factors associated with the exam procedures' and 'Exam invigilation'. The overall satisfaction was high for both staff and students (higher for students and female staff). Students with previous experience in online exams scored more positively than first-year students. University support, process-related stress and e-invigilation were highlighted. CONCLUSIONS: The overall satisfaction with the e-exams was high, despite the technical problems, time-consuming processes and related stress. University support (training, IT support and resources) and mock exams emerged as important elements of online exams, as was the e-invigilation, which students perceived as efficient and non-intrusive.

Awareness of Forensic Odontology among Dental Students and Faculty in Cyprus: A Survey-Based Study.

This study aimed to evaluate the awareness, comprehension, and practices concerning forensic odontology among dental students and faculty at a Dental School in Cyprus. An online, cross-sectional, descriptive survey, employing an adapted, self-administered questionnaire, was disseminated to all dental students and faculty at the School of Dentistry, European University Cyprus, in November 2022. The survey assessed participants' demographic information and explored their awareness with questions alluding to knowledge, attitudes and practices in forensic dentistry. Of those surveyed, 47 faculty members and 304 students responded, yielding response rates of 66.2% and 80%, respectively. Statistical analysis, including Kendall's tau test and χ2 test were employed to examine correlations and associations, with Cramer's V used to measure the strength of significant associations. The predetermined significance level was α = 0.05. Awareness levels were assessed through participants' responses to specific questions in the survey. It was revealed that 87% of faculty and 65% of students were familiar with forensic odontology. A noteworthy 94% of faculty and 85% of students recognized teeth as DNA repositories. A high percentage, 98% of faculty and 89% of students, acknowledged the role of forensic odontology in the identification of criminals and deceased individuals. Awareness of age estimation through dental eruption patterns was evident in 85% of faculty and 81.6% of students. A substantial proportion (80% of faculty) maintained dental records, while 78% of students recognized the importance of dental record-keeping in ensuring quality care. Interestingly, 57% of students and 64% of faculty were aware of the possibility of dentists testifying as expert witnesses. The majority, 95.7% of faculty and 85% of students, concurred that physical harm, scars, and behavioral alterations predominantly indicate child abuse. The findings, revealing robust awareness among respondents, underscore the importance of enhancing faculty engagement in relevant seminars to further strengthen their knowledge. Additionally, emphasizing improved record-keeping practices for potential forensic applications emerges as a crucial aspect. These insights have implications for refining dental education in Cyprus and enhancing forensic practices by promoting ongoing professional development and emphasizing meticulous record-keeping within the dental community.