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AIM: Chatbot Generative Pre-trained Transformer (ChatGPT) is a generative artificial intelligence (AI) software based on large language models (LLMs), designed to simulate human conversations and generate novel content based on the training data it has been exposed to. The aim of this study was to evaluate the consistency and accuracy of ChatGPT-generated answers to clinical questions in endodontics, compared to answers provided by human experts. METHODOLOGY: Ninety-one dichotomous (yes/no) questions were designed and categorized into three levels of difficulty. Twenty questions were randomly selected from each difficulty level. Sixty answers were generated by ChatGPT for each question. Two endodontic experts independently answered the 60 questions. Statistical analysis was performed using the SPSS program to calculate the consistency and accuracy of the answers generated by ChatGPT compared to the experts. Confidence intervals (95%) and standard deviations were used to estimate variability. RESULTS: The answers generated by ChatGPT showed high consistency (85.44%). No significant differences in consistency were found based on question difficulty. In terms of answer accuracy, ChatGPT achieved an average accuracy of 57.33%. However, significant differences in accuracy were observed based on question difficulty, with lower accuracy for easier questions. CONCLUSIONS: Currently, ChatGPT is not capable of replacing dentists in clinical decision-making. As ChatGPT's performance improves through deep learning, it is expected to become more useful and effective in the field of endodontics. However, careful attention and ongoing evaluation are needed to ensure its accuracy, reliability and safety in endodontics.
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Inteligência Artificial , Software , Humanos , Reprodutibilidade dos Testes , Tomada de Decisão Clínica , Assistência OdontológicaRESUMO
STATEMENT OF PROBLEM: The artificial intelligence (AI) software program ChatGPT is based on large language models (LLMs) and is widely accessible. However, in prosthodontics, little is known about its performance in generating answers. PURPOSE: The purpose of this study was to determine the performance of ChatGPT in generating answers about removable dental prostheses (RDPs) and tooth-supported fixed dental prostheses (FDPs). MATERIAL AND METHODS: Thirty short questions were designed about RDPs and tooth-supported FDP, and 30 answers were generated for each of the questions using ChatGPT-4 in October 2023. The 900 generated answers were independently graded by experts using a 3-point Likert scale. The relative frequency and absolute percentage of answers were described. Accuracy was assessed using the Wald binomial method, while repeatability was evaluated using percentage agreement, Brennan and Prediger coefficient, Conger generalized Cohen kappa, Fleiss kappa, Gwet AC, and Krippendorff alpha methods. Confidence intervals were set at 95%. Statistical analysis was performed using the STATA software program. RESULTS: The performance of ChatGPT in generating answers related to RDP and tooth-supported FDP was limited. The answers showed a reliability of 25.6%, with a confidence range between 22.9% and 28.6%. The repeatability ranged from substantial to moderate. CONCLUSIONS: The results show that currently ChatGPT has limited ability to generate answers related to RDPs and tooth-supported FDPs. Therefore, ChatGPT cannot replace a dentist, and, if professionals were to use it, they should be aware of its limitations.
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Inteligência Artificial , Prostodontia , Reprodutibilidade dos Testes , Projetos de Pesquisa , SoftwareRESUMO
INTRODUCTION: This study investigates the behavior of graphene and GUM in terms of cyclic fatigue resistance and torsion through a finite element analysis on a file with an eccentric rectangular cross section and variable taper, and on a file with a centered triangular cross section, constant taper, and constant pitch. METHODS: Root canals and endodontic files were created using Catia V5R21 software. For torsional analysis, the tip of the file was fixed at 1 and 3 mm, and a moment of 2.5 N-mm was generated at the handle. For the bending analysis in curved canals (45° and 60°), the handle was kept fixed and a force of 1 N was applied at the tip while the file was kept fixed at 9 mm. RESULTS: GUM metal instruments showed better torsional resistance. On the other hand, NiTi and graphene performed better under the applied loads during flexion at 45° and 60°. CONCLUSION: GUM metal is emerging as a promising material in the field of endodontic instrument design due to its physical properties.
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Grafite , Estresse Mecânico , Análise de Elementos Finitos , Níquel , Titânio , Preparo de Canal Radicular , Teste de Materiais , Metais , Desenho de EquipamentoRESUMO
Dental wear arises from mechanical (attrition or abrasion) and chemical (erosion) factors. Despite its prevalence and clinical significance, accurately measuring and understanding its causes remain challenging in everyday practice. This one-year study with 39 participants involved comprehensive examinations and full-arch intraoral scans at the start and after 12 months. Volume loss exceeding 100 µ on each tooth's surfaces (buccal, lingual/palatine and incisal/occlusal) was measured by comparing three-dimensional scans from both time points. This study also assessed factors such as abrasion and erosion through clinical exams and questionnaires. There were no significant differences in dental wear in participants with sleep bruxism. However, noticeable wear occurred in the front teeth of those with waking bruxism and joint-related symptoms. Increased wear was associated with frequent consumption of acidic drinks, regular swimming, dry mouth, nocturnal drooling and heartburn, while no significant wear was found in patients with reflux. The used methodology proved effective in accurately assessing the progression of dental wear, which is important as many patients may initially be asymptomatic. The variability observed in dental wear patterns underscores the need to develop specific software applications that allow immediate and efficient comparison of wear areas based on extensive analysis of patient databases.
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AI has revolutionized the way we interact with technology. Noteworthy advances in AI algorithms and large language models (LLM) have led to the development of natural generative language (NGL) systems such as ChatGPT. Although these LLM can simulate human conversations and generate content in real time, they face challenges related to the topicality and accuracy of the information they generate. This study aimed to assess whether ChatGPT-4 could provide accurate and reliable answers to general dentists in the field of oral surgery, and thus explore its potential as an intelligent virtual assistant in clinical decision making in oral surgery. Thirty questions related to oral surgery were posed to ChatGPT4, each question repeated 30 times. Subsequently, a total of 900 responses were obtained. Two surgeons graded the answers according to the guidelines of the Spanish Society of Oral Surgery, using a three-point Likert scale (correct, partially correct/incomplete, and incorrect). Disagreements were arbitrated by an experienced oral surgeon, who provided the final grade Accuracy was found to be 71.7%, and consistency of the experts' grading across iterations, ranged from moderate to almost perfect. ChatGPT-4, with its potential capabilities, will inevitably be integrated into dental disciplines, including oral surgery. In the future, it could be considered as an auxiliary intelligent virtual assistant, though it would never replace oral surgery experts. Proper training and verified information by experts will remain vital to the implementation of the technology. More comprehensive research is needed to ensure the safe and successful application of AI in oral surgery.