JDSE

The Journal of Dental Sciences and Education deals with General Dentistry, Pediatric Dentistry, Restorative Dentistry, Orthodontics, Oral diagnosis and DentomaxilloFacial Radiology, Endodontics, Prosthetic Dentistry, Periodontology, Oral and Maxillofacial Surgery, Oral Implantology, Dental Education and other dentistry fields and accepts articles on these topics. Journal of Dental Science and Education publishes original research articles, review articles, case reports, editorial commentaries, letters to the editor, educational articles, and conference/meeting announcements.

EndNote Style
Index
Original Article
A multidisciplinary evaluation of AI-powered chatbots on apical root-end resection: assessing alignment with international endodontic guidelines-a comparative methodological study
Aims: This study aimed to identify the clinically relevant patient questions about apical root-end resection based on international consensus guidelines, and to systematically evaluate the accuracy, quality, usefulness, and readability of generated responses by four Artificial Intelligence (AI)-powered conversational agents, ChatGPT-4, DeepSeek V3.1, Gemini 3, and Copilot.
Methods: A standardized set of 20 clinical questions was developed from the American Association of Endodontists guidelines and international consensus reports. A priori, an evidence-based answer key was established as the reference standard. Queries were submitted to ChatGPT-4, DeepSeek V3.1, Gemini 3, and Copilot, following a standardized interaction protocol designed to minimize personalization and carryover effects, such as incognito mode, newly created accounts, and no response regeneration. The outputs were independently assessed by three experts in periodontics and oral radiology, using validated tools, such as CLEAR criteria, modified Global Quality Score (mGQS), accuracy ratings, DISCERN, readability indices (Flesch reading ease, FRE and Flesch-Kincaid grade level, FKGL) and the patient education materials assessment tool (PEMAT).
Results: ChatGPT-4 and Copilot achieved significantly higher CLEAR scores than Gemini 3. Copilot achieved significantly higher mGQS and accuracy than DeepSeek V3.1 and Gemini 3 and received significantly lower, and therefore more favorable, usefulness scores. Gemini 3 scored higher on the FKGL test and lower on the understandability test compared to DeepSeek V3.1. Relationships between evaluation metrics were different between models.
Conclusion: The AI models evaluated demonstrated significant variability in clinical accuracy, quality, readability, and patient-centered usability. Copilot had the best overall mGQS and Accuracy scores and the best Usefulness scores, while the models varied in their strengths in readability, understandability, and actionability.


1. Möller AJ, Fabricius L, Dahlén G, et al. Influence on periapical tissues of indigenous oral bacteria and necrotic pulp tissue in monkeys. Scand J Dent Res. 1981;89(6):475-484. doi:10.1111/j.1600-0722.1981.tb01711.x
2. Song M, Nam T, Shin SJ, Kim E. Comparison of clinical outcomes of endodontic microsur-gery: 1 year versus long-term follow-up. J Endod. 2014;40(4):490-494. doi:10.1016/j.joen.2013.10.034
3. Setzer FC, Shah SB, Kohli MR, Karabucak B, Kim S. Outcome of endodontic surgery: a me-ta-analysis of the literature-part 1: comparison of traditional root-end surgery and endodon-tic microsurgery. J Endod. 2010;36(11):1757-1765. doi:10.1016/j.joen.2010.08.007
4. American Association of Endodontists. Glossary of Endodontic Terms. 10th ed. American Association of Endodontists; 2020.
5. Berman LH, Hargreaves KM. Cohen’s Pathways of the Pulp. 12th ed. Elsevier; 2020.
6. Jiang F, Jiang Y, Zhi H, et al. Artificial Intelligence in healthcare: past, present and future. Stroke Vasc Neurol. 2017;2(4):230-243. doi:10.1136/svn-2017-000101
7. Schwendicke F, Samek W, Krois J. Artificial Intelligence in dentistry: chances and challeng-es. J Dent Res. 2020;99(7):769-774. doi:10.1177/0022034520915714
8. Keleş A, Keskin C. A micro-computed tomographic study of band-shaped root canal isth-muses, having their floor in the apical third of mesial roots of mandibular first molars. Int Endod J. 2018;51(2):240-246. doi:10.1111/iej.12842
9. Xu T, Fan W, Tay FR, et al. Micro-computed tomographic evaluation of the prevalence, dis-tribution, and morphologic features of accessory canals in Chinese permanent teeth. J En-dod. 2019;45(8):994-999. doi:10.1016/j.joen.2019.04.001
10. Ordinola-Zapata R, Martins JNR, Niemczyk S, Bramante CM. Apical root canal anatomy in the mesiobuccal root of maxillary first molars: influence of root apical shape and prevalence of apical foramina-a micro-CT study. Int Endod J. 2019;52(8):1218-1227. doi:10.1111/iej.13109
11. Xu T, Tay FR, Gutmann JL, et al. Micro-computed tomography assessment of apical acces-sory canal morphologies. J Endod. 2016;42(5):798-802. doi:10.1016/j.joen.2016.02.006
12. Stropko JJ, Doyon GE, Gutmann JL. Root-end management: resection, cavity preparation, and material placement. Endod Topics. 2005;11(1):131-151. doi:10.1111/j.1601-1546.2005.00158.x
13. Thurzo A, Urbanová W, Novák B, et al. Where is the Artificial Intelligence applied in dentis-try? Systematic review and literature analysis. Healthcare (Basel). 2022;10(7):1269. doi:10.3390/healthcare10071269
14. Esmailpour H, Rasaie V, Babaee Hemmati Y, Falahchai M. Performance of Artificial Intelli-gence chatbots in responding to the frequently asked questions of patients regarding dental prostheses. BMC Oral Health. 2025;25(1):574. doi:10.1186/s12903-025-05965-9
15. Jacobs T, Shaari A, Gazonas CB, Ziccardi VB. Is ChatGPT an accurate and readable patient aid for third molar extractions? J Oral Maxillofac Surg. 2024;82(10):1239-1245. doi:10.1016/j.joms.2024.06.177
16. Ceylan Şen S, Çardakci Bahar Ş, Saraç Atagün Ö, et al. Quality and reliability of AI infor-mation on dental implant failure: a comparative multi-model analysis. J Craniofac Surg. 2026;37(3-4):675-680. doi:10.1097/SCS.0000000000012415
17. Özcivelek T, Özcan B. Comparative evaluation of responses from DeepSeek-R1, ChatGPT-o1, ChatGPT-4, and dental GPT chatbots to patient inquiries about dental and maxillofacial prostheses. BMC Oral Health. 2025;25(1):871. doi:10.1186/s12903-025-06267-w
18. Ceylan Şen S, Saraç Atagün Ö, Ustaoğlu G, et al. Do AI chatbots tell the truth about dentin hypersensitivity? A comparative evaluation of quality, accuracy, and readability. Cumhuriyet Dent J. 2026;29(1):138-147. doi:10.7126/cumudj.1848545
19. Helvacioglu-Yigit D, Demirturk H, Ali K, et al. Evaluating Artificial Intelligence chatbots for patient education in oral and maxillofacial radiology. Oral Surg Oral Med Oral Pathol Oral Radiol. 2025;139(6):750-759. doi:10.1016/j.oooo.2025.01.001
20. National Library of Medicine. How to write easy-to-read health materials. Updated Novem-ber 2020. Accessed December 12, 2022. https://medlineplus.gov/all_easytoread.html
21. Sallam M, Barakat M, Sallam M. Pilot testing of a tool to standardize the assessment of the quality of health information generated by Artificial Intelligence-based models. Cureus. 2023;15(11):e49373. doi:10.7759/cureus.49373
22. Bernard A, Langille M, Hughes S, et al. A systematic review of patient inflammatory bowel disease information resources on the World Wide Web. Am J Gastroenterol. 2007;102(9):2070-2077. doi:10.1111/j.1572-0241.2007.01325.x
23. Hatia A, Doldo T, Parrini S, et al. Accuracy and completeness of ChatGPT-generated infor-mation on interceptive orthodontics: a multicenter collaborative study. J Clin Med. 2024;13(3):735. doi:10.3390/jcm13030735
24. Yeo YH, Samaan JS, Ng WH, et al. Assessing the performance of ChatGPT in answering questions regarding cirrhosis and hepatocellular carcinoma. Clin Mol Hepatol. 2023;29(3):721-732. doi:10.3350/cmh.2023.0089
25. Alnsour MM, Alenezi R, Barakat M, et al. Assessing ChatGPT’s suitability in responding to the public’s inquires on the effects of smoking on oral health. BMC Oral Health. 2025;25(1):1207. doi:10.1186/s12903-025-06377-5
26. Büker M, Mercan G. Readability, accuracy and appropriateness and quality of AI chatbot responses as a patient information source on root canal retreatment: a comparative assess-ment. Int J Med Inform. 2025;201:105948. doi:10.1016/j.ijmedinf.2025.105948
27. Bahadir HS, Keskin NB, Çakmak EŞK, et al. Patients’ attitudes toward Artificial Intelligence in dentistry and their trust in dentists. Oral Radiol. 2025;41(1):52-59. doi:10.1007/s11282-024-00775-1
28. Kosan E, Krois J, Wingenfeld K, et al. Patients’ perspectives on Artificial Intelligence in dentistry: a controlled study. J Clin Med. 2022;11(8):2143. doi:10.3390/jcm11082143
29. Alqutaibi AY, Algabri RS, Alamri AS, et al. Advancements of Artificial Intelligence algo-rithms in predicting dental implant prognosis from radiographic images: a systematic re-view. J Prosthet Dent. 2025;134(6):2177-2188. doi:10.1016/j.prosdent.2024.10.036
30. Mugri MH. Accuracy of Artificial Intelligence models in detecting peri-implant bone loss: a systematic review. Diagnostics (Basel). 2025;15(6):655. doi:10.3390/diagnostics15060655
31. Durmazpinar PM, Ekmekci E. Comparing diagnostic skills in endodontic cases: dental stu-dents versus ChatGPT-4o. BMC Oral Health. 2025;25(1):457. doi:10.1186/s12903-025-05857-y
32. Ekmekci E, Durmazpinar PM. Evaluation of different Artificial Intelligence applications in responding to regenerative endodontic procedures. BMC Oral Health. 2025;25(1):53. doi:10.1186/s12903-025-05424-5
33. Terzi M, Yavuz MC, Bicer T, Buyuk SK. Evaluation of Artificial Intelligence robot’s knowledge and reliability on dental implants and peri-implant phenotype. Sci Rep. 2025;15(1):9519. doi:10.1038/s41598-025-94576-z
34. Yau JYS, Saadat S, Hsu E, et al. Accuracy of prospective assessments of 4 large language model chatbot responses to patient questions about emergency care: experimental compara-tive study. J Med Internet Res. 2024;26:e60291. doi:10.2196/60291
35. Dursun D, Bilici Geçer R. Can Artificial Intelligence models serve as patient information consultants in orthodontics? BMC Med Inform Decis Mak. 2024;24(1):211. doi:10.1186/s12911-024-02619-8
Volume 4, Issue 3, 2026
Page : 76-83
_Footer