ArticleBMC oral health2025
Comparison of responses from different artificial intelligence-powered chatbots regarding the All-on-four dental implant concept.
Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
13 citing papers in PubMed.
- Effect of artificial intelligence-assisted personalized feedback on radiographic diagnostic performance of dental students: a controlled study.BMC medical education · 2025Trial
- Development and validation of a human-supervised AI-augmented living oncology evidence platform: a breast cancer pilot study.ESMO real world data and digital oncology · 2026Article
- Comparison of artificial intelligence-based chatbots and expert periodontists in responding to patient questions: a multi-dimensional analysis.BMC oral health · 2026Article
- Accuracy and empathy of AI-based conversational chatbots in response to temporomandibular dysfunction related queries.PEC innovation · 2026Article
- Large language models in implant dentistry: a scoping review of applications, performance, and limitations.BMC oral health · 2026Article
- Generative AI vs web search for patient education: a comparative evaluation of OSA information quality.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2026Article
- A context-augmented large language model for accurate precision oncology medicine recommendations.Cancer cell · 2026Article
- Comparative assessment of quality, consistency, and reference accuracy of MIH-related clinical information generated by ChatGPT-4o and DeepSeek R1.BMC oral health · 2026Article
- Assessing the accuracy, reliability, quality, and readability of artificial intelligence chatbots in patient education: insights from zirconia crowns.BMC oral health · 2026Article
- Digital Dentistry in Clinical Practice: A Scoping Review of Current Capabilities and Future Directions.International dental journal · 2026Article
- Evaluating AI Chatbots in Prosthodontics Education: A Quantitative MCQ-Based Assessment.International journal of dentistry · 2026Article
- Comparison of the performances of different updated generative artificial intelligence models on the Japanese National Dental Examination.Journal of dental sciences · 2026Article
- Knowledge-level comparison in pulpal and periapical diseases: dental students versus artificial intelligence models (Gemini, Microsoft Copilot, ChatGPT-3.5, ChatGPT-4o): cross-sectional study.BMC medical education · 2025Article
Corrections and comments
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Authors and funding
1 author.
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Abstract
backgroundRecent advancements in Artificial Intelligence (AI) have transformed the healthcare field, particularly through chatbots like ChatGPT, OpenEvidence, and MediSearch. These tools analyze complex data to aid clinical decision-making, enhancing efficiency in diagnosis, treatment planning, and patient management. When applied in the "All-on-Four" dental implant concept, AI facilitates immediate prosthetic restorations and meets the demand for expert guidance. This integration boosts the long-term success of surgical outcomes by providing real-time support and improving patient education and postoperative satisfaction. This study aimed to evaluate the effectiveness of three AI-powered chatbots-ChatGPT 4.0, OpenEvidence, and MediSearch-in answering frequently asked questions regarding the All-on-Four dental implant concept.
methodThis study investigated the response accuracy of three AI-powered chatbots to common queries about the All-on-Four dental implant concept. Using alsoasked.com, twenty pertinent questions-ten patient-focused and ten technical-were identified. Oral and maxillofacial surgeons evaluated the chatbot responses using a 5-point Likert scale. Statistical analysis was performed with the Kruskal-Wallis test, supplemented by pairwise Mann-Whitney U tests with Bonferroni correction, to assess the significance of differences among the chatbots' performances.
resultsThe Kruskal-Wallis test showed statistically significant differences between the three chatbots for both patient and technical questions (p < 0.01). Pairwise comparisons were evaluated using the Mann-Whitney U test. While significant differences were found among each chatbot for patient questions, no significant difference was observed between ChatGPT and MediSearch for technical questions (p = 0.158). When comparing responses of the same chatbot to patient and technical questions, it was found that MediSearch performed better in technical questions (p < 0.001).
conclusionAdvancements in technology have made AI-powered chatbots an inevitable influence in specialized medical fields such as Oral, Maxillofacial Surgery. Our findings indicate that these chatbots can provide valuable information for patients undergoing medical procedures and serve as a resource for healthcare professionals.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.