JRM
Journal of Radiology in Medicine

Journal of Radiology in Medicine is an international journal that published original research and articles in all areas of radiology. Its publishes original research articles, review articles, case reports, editorial commentaries, letters to the editor, educational articles, and conference/meeting announcements.

eISSN: 3023-6487
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Original Article
Comparison of chatbots for patient information on head and neck imaging techniques in terms of scientific quality and readability
Abstract
Aims: This study aimed to evaluate the scientific quality and readability of the responses of ChatGPT and Microsoft Copilot to patient questions about head and neck imaging methods in dentistry.
Methods: Twenty patient-focused questions were directed to both chatbots. Responses were evaluated independently by two experts using a 7-point Likert scale, and readability levels were analyzed using the Flesch Reading Ease Score and Flesch-Kincaid Grade Level (FKGL) indices. Inter-expert agreement was assessed using Cohen’s Kappa, and differences between chatbots were assessed using an independent-samples t-test.
Results: Statistically significant but weak agreement was observed among experts (κ=0.399, p<0.001). No significant difference was found between ChatGPT and Microsoft Copilot in terms of Flesch Reading Ease Score index and expert scores (p>0.05). However, FKGL scores were significantly higher in Microsoft Copilot (p=0.025), indicating more linguistically complex responses.
Conclusion: ChatGPT and Microsoft Copilot demonstrated similar scientific quality and readability based on FRES scores. However, Microsoft Copilot generated more linguistically complex responses than ChatGPT, as reflected by its significantly higher FKGL scores, indicating that a higher educational level may be required for comprehension. In conclusion, AI-based chatbots can be useful as supportive tools in patient information and education, but expert supervision remains crucial in this area.

Keywords : Artificial intelligence, chatbots, patient education as topic, radiologic health

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1. Guler R, Yalcin E. Performance of AI chatbots in preliminary diagnosis of maxillofacial pathologies. Med Sci Monit. 2025;31:e949076. doi:10.12659/MSM.949076
2. Thirunavukarasu AJ, Ting DSJ, Elangovan K, Gutierrez L, Tan TF, Ting DSW. Large language models in medicine. Nat Med. 2023;29(8):1930-1940. doi:10.1038/s41591-023-02448-8
3. Çetin P, Onan A. Büyük dil modellerinin tıp eğitimde soru yanıtlama sistemlerinde kullanımı: potansiyel, zorluklar ve gelecek yönelimleri. JISMCE. 2025;1(1):82-108.
4. Rokhshad R, Zhang P, Mohammad-Rahimi H, Pitchika V, Entezari N, Schwendicke F. Accuracy and consistency of chatbots versus clinicians for answering pediatric dentistry questions: a pilot study. J Dent. 2024; 144:104938. doi:10.1016/j.jdent.2024.104938
5. Tan S, Xin X, Wu D. ChatGPT in medicine: prospects and challenges: a review article. Int J Surg. 2024;110(6):3701-3706. doi:10.1097/JS9.0000000000001312
6. Jeong H, Han SS, Yu Y, Kim S, Jeon KJ. How well do large language model-based chatbots perform in oral and maxillofacial radiology? Dentomaxillofac Radiol. 2024;53(6):390-395. doi:10.1093/dmfr/twae021
7. Zhang Y, Lu X, Luo Y, Zhu Y, Ling W. Performance of Artificial Intelligence chatbots on ultrasound examinations: cross-sectional comparative analysis. JMIR Med Inform. 2025;13:e63924. doi:10.2196/63924
8. Patil NS, Huang RS, Caterine S, et al. Artificial Intelligence chatbots’ understanding of the risks and benefits of computed tomography and magnetic resonance imaging scenarios. Can Assoc Radiol J. 2024;75(3): 518-524. doi:10.1177/08465371231220561
9. Mohammad-Rahimi H, Khoury ZH, Alamdari MI, et al. Performance of AI chatbots on controversial topics in oral medicine, pathology, and radiology. Oral Surg Oral Med Oral Pathol Oral Radiol. 2024;137(5):508-514. doi:10.1016/j.oooo.2024.01.015
10. Reda R, Zanza A, Mazzoni A, Cicconetti A, Testarelli L, Di Nardo D. An update of the possible applications of magnetic resonance imaging (MRI) in dentistry: a literature review. J Imaging. 2021;7(5):75. doi:10.3390/jimaging7050075
11. Al-Haj Husain A, Zollinger M, Stadlinger B, et al. Magnetic resonance imaging in dental implant surgery: a systematic review. Int J Implant Dent. 2024;10(1):14. doi:10.1186/s40729-024-00532-3

Article available in :
Volume 3, Issue 3, 2026
Page : 54-58
https://doi.org/10.51271/JRM-0051
Article Information
Received : 15 Haz 2026
Accepted : 17 Ağu 2026
Published : 19 Eyl 2026
Corresponding Author :

Meltem Horoz: Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Kırıkkale University, Kırıkkale, Turkiye

[email protected]
Citation : Horoz M, Cavnar A. Comparison of chatbots for patient information on head and neck imaging techniques in terms of scientific quality and readability. J Radiol Med. 2026;3(3):54-58. doi:10.51271/JRM-0051

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