Öz
Amaç: Yapay zeka (YZ) sohbet robotları, hastaların sorularına insan benzeri yanıtlar vererek hasta eğitiminde kullanılma potansiyeline sahiptir. Ancak protetik diş tedavisinin önemli bir unsuru olan implant destekli protezlerin kullanımı ve bakımı ile ilgili doğru bilgi verme konusundaki güvenilirlikleri ile ilgili bilgiler sınırlıdır. Bu çalışma altı YZ sohbet robotunun implant destekli protezlerle ilgili yanıtlarının güncel literatürle uyumunu değerlendirmeyi amaçlamaktadır.
Gereç ve Yöntem: İmplant destekli protezlerin kullanımı ve bakımıyla ilgili 25 soru, ChatGPT-4, ChatGPT 01-Preview, ChatGPT 01-Mini, Gemini Advanced, Co-pilot ve Claude 3.5 Sonnet olmak üzere altı YZ sohbet robotuna yöneltildi. Yanıtların doğruluğu iki protez uzmanı tarafından beş puanlık Likert ölçeği kullanılarak değerlendirildi ve ortalama puanlar hesaplandı. Sohbet robotları arasındaki farklılıklar tek yönlü ANOVA testi ile analiz edilmiş ve anlamlılık düzeyi α=0.05 olarak belirlenmiştir. Post-hoc karşılaştırma testi olarak Tamhane’nin T2 testi kullanılmıştır.
Bulgular: Altı YZ sohbet robotunun implant destekli protezlerin kullanımı ve bakımıyla ilgili sorulara verdiği yanıtların doğruluğu ve ilgi düzeyi değerlendirildi. Doğruluk açısından ChatGPT 01-Preview en yüksek ortalama puanı (4.80±0.08) alırken, Copilot en düşük puanı aldı (3.22±0.20). ANOVA ve Tamhane’nin
T2 testleri modeller arasında istatistiksel olarak anlamlı farklar ortaya koydu (p<0.05). İlgi düzeyinde ise Claude 3.5 Sonnet en yüksek ortalama puanı (4.94±0.17) alırken, Co-pilot en düşük performansı gösterdi (4.12±0.59).
Sonuç: YZ sohbet robotlarının, implant destekli protezler konusunda verdiği yanıtlar hasta eğitiminde kullanılabileceğini göstermektedir. Ancak, yanıtlardaki bazı yanlışlıklar ve Copilot’un yetersiz performansı bu teknolojilerin kullanımında insan denetiminin gerekliliğini ortaya koymaktadır.
Anahtar Kelimeler
Yapay zeka Sohbet robotu Dijital sağlık Hasta eğitimi Dental implant
Kaynakça
- Alghamdi HS, Jansen JA. The development and future of dental implants. Dent Mater J 2020;39:167-72.
- Buser D, Sennerby L, De Bruyn H. Modern implant dentistry based on osseointegration: 50 years of progress, current trends and open questions. Periodontol 2000 2017;73:7-21.
- Monje A, Aranda L, Diaz KT, Alarcón MA, Bagramian RA, Wang HL, et al. Impact of maintenance Therapy for the prevention of peri-implant diseases: A systematic review and meta-analysis. J Dent Res 2016;95:372-9.
- Ferro AS, Nicholson K, Koka S. Innovative trends in implant dentistry training and education: a narrative review. J Clin Med 2019;8:16-8.
- Pulcini A, Bollaín J, Sanz-Sánchez I, Figuero E, Alonso B, Sanz M, et al. Clinical effects of the adjunctive use of a 0.03% chlorhexidine and 0.05% cetylpyridinium chloride mouth rinse in the management of peri-implant diseases: A randomized clinical trial. J Clin Periodontol 2019; 46:342-53.
- Walia K, Belludi SA, Kulkarni P, Darak P, Swamy S. A comparative and a qualitative analysis of patient’s motivations, expectations and satisfaction with dental implants. J Clin Diagn Res 2016;10:23-6. Menziletoglu D, Guler AY, Isik BK. Are YouTube videos related to dental implant useful for patient education? J Stomatol Oral Maxillofac Surg 2020;121:661-4.
- Ahuja AS. The impact of artificial intelligence in medicine on the future role of the physician. Peer J 2019; 4;7:e7702.
- Reyes TR, Knorst JK, Ortiz FR, Ardenghi TM. Scope and challenges of machine learning-based diagnosis and prognosis in clinical dentistry: A literature review. J of Clin Transl Res 2021;7:523-39.
- Berge TI. Public awareness, information sources and evaluation of oral implant treatment in Norway. Clin Oral Implants Res 2000;11:401-8.
- Yurdakurban E, Topsakal KG, Duran GS. A comparative analysis of AI-based chatbots: Assessing data quality in orthognathic surgery related patient information. J Stomatol Oral Maxillofac Surg 2024;125:101757.
- Polizzi A, Quinzi V, Lo Giudice A, Marzo G, Leonardi R, Isola G. Accuracy of artificial intelligence models in the prediction of periodontitis: A systematic review. JDR Clin Trans Res 2024;9:312-24.
- 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;82:1239-45.
- Dursun D, Bilici Geçer R. Can artificial intelligence models serve as patient information consultants in orthodontics? BMC Med Inform Decis Mak 2024;24:211.
- Ghosh A, Saha AP, Saha S, Das A. Promoting the importance of recall visits among dental patients in India using a semiautonomous AI system. Stud Health Technol Inform 2022;16:85-92.
- Di Battista M, Kernitsky J, Dibart S. Artificial intelligence chatbots in patient communication: current possibilities. Int J Periodontics Restorative Dent 2024;44:731-8.
- Lyle DM. Implant maintenance: is there an ideal approach? Compend Contin Educ Dent 2013;34:386-90.
- Kracher CM, Smith WS. Oral health maintenance dental implants. Dent Assist 2010;79:27-35.
- Louropoulou A, Slot DE, Van der Weijden F. Mechanical self-performed oral hygiene of implant supported restorations: a systematic review. J Evid Based Dent Pract 2014;14:60-9.
- Carra MC, Blanc-Sylvestre N, Courtet A, Bouchard P. Primordial and primary prevention of peri-implant diseases: A systematic review and meta-analysis. J Clin Periodontol 2023;50:77-112.
- Banerjee, TN, Paul P, Debnath A, Banerjee S. Unveiling the prospects and challenges of artificial intelligence in implant dentistry. A systematic review. J Osseointegration 2024; 16: 53-60.
- Shehab AA, Shedd KE, Alamah W, Mardini S, Bite U, Gibreel W. Bridging gaps in health literacy for cleft lip and palate: The role of artificial intelligence and interactive educational materials. The Cleft Palate Craniofacial J 2024;9:1-7.
- Reading K, Knowles L, Towns S. The hygienist’s role in the management of the implant patient in primary care. Prim Dent J 2024;3:53-62.
Do Artificial Intelligence Chatbots Provide Adequate Information to Patients Using Implant-Supported Prostheses?
Öz
Aim: Artificial intelligence (AI) chatbots hold promise with regard to patient education because of their ability to deliver human-like responses to inquiries, yet their reliability in providing accurate information on the use and care of implant-supported prostheses – a critical aspect of prosthodontics – remains uncertain. This study sought to assess the alignment of responses from six AI chatbots to questions on this topic with the current literature on implant-supported prostheses.
Materials and Method: Twenty-five questions related to the usage and maintenance of implant-supported prostheses were posed to six AI chatbots: ChatGPT-4, ChatGPT 01-Preview, ChatGPT 01-Mini, Gemini Advanced, Co-pilot, and Claude 3.5 Sonnet. The accuracy of their responses was assessed by two
prosthodontists using a five-point Likert scale, and the average scores were calculated. Differences among the chatbots were analyzed using one-way ANOVA, with the significance level set at α=0.05. As the post-hoc comparison test, Tamhane’s T2 test was used.
Results: The accuracy and relevance of the responses provided by the six AI chatbots to questions about the maintenance and use of implant-supported prostheses were evaluated. In terms of accuracy, ChatGPT 01-Preview achieved the highest mean score (4.80±0.08), while Co-pilot received the lowest score (3.22±0.20). ANOVA and Tamhane’s T2 tests revealed statistically significant differences between the models (p<0.05). Regarding relevance, Claude 3.5 Sonnet obtained the highest mean score (4.94±0.17), whereas Co-pilot demonstrated the worst performance (4.12±0.59).
Conclusion: AI chatbots can serve as effective tools for patient education about implant-supported prostheses. However, inaccuracies in the responses given by certain models and the suboptimal performance of Co-pilot highlight the necessity for human oversight when utilizing these technologies.
Anahtar Kelimeler
Artificial intelligence Chatbot Dental implant Digital health Patient education.
Kaynakça
- Alghamdi HS, Jansen JA. The development and future of dental implants. Dent Mater J 2020;39:167-72.
- Buser D, Sennerby L, De Bruyn H. Modern implant dentistry based on osseointegration: 50 years of progress, current trends and open questions. Periodontol 2000 2017;73:7-21.
- Monje A, Aranda L, Diaz KT, Alarcón MA, Bagramian RA, Wang HL, et al. Impact of maintenance Therapy for the prevention of peri-implant diseases: A systematic review and meta-analysis. J Dent Res 2016;95:372-9.
- Ferro AS, Nicholson K, Koka S. Innovative trends in implant dentistry training and education: a narrative review. J Clin Med 2019;8:16-8.
- Pulcini A, Bollaín J, Sanz-Sánchez I, Figuero E, Alonso B, Sanz M, et al. Clinical effects of the adjunctive use of a 0.03% chlorhexidine and 0.05% cetylpyridinium chloride mouth rinse in the management of peri-implant diseases: A randomized clinical trial. J Clin Periodontol 2019; 46:342-53.
- Walia K, Belludi SA, Kulkarni P, Darak P, Swamy S. A comparative and a qualitative analysis of patient’s motivations, expectations and satisfaction with dental implants. J Clin Diagn Res 2016;10:23-6. Menziletoglu D, Guler AY, Isik BK. Are YouTube videos related to dental implant useful for patient education? J Stomatol Oral Maxillofac Surg 2020;121:661-4.
- Ahuja AS. The impact of artificial intelligence in medicine on the future role of the physician. Peer J 2019; 4;7:e7702.
- Reyes TR, Knorst JK, Ortiz FR, Ardenghi TM. Scope and challenges of machine learning-based diagnosis and prognosis in clinical dentistry: A literature review. J of Clin Transl Res 2021;7:523-39.
- Berge TI. Public awareness, information sources and evaluation of oral implant treatment in Norway. Clin Oral Implants Res 2000;11:401-8.
- Yurdakurban E, Topsakal KG, Duran GS. A comparative analysis of AI-based chatbots: Assessing data quality in orthognathic surgery related patient information. J Stomatol Oral Maxillofac Surg 2024;125:101757.
- Polizzi A, Quinzi V, Lo Giudice A, Marzo G, Leonardi R, Isola G. Accuracy of artificial intelligence models in the prediction of periodontitis: A systematic review. JDR Clin Trans Res 2024;9:312-24.
- 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;82:1239-45.
- Dursun D, Bilici Geçer R. Can artificial intelligence models serve as patient information consultants in orthodontics? BMC Med Inform Decis Mak 2024;24:211.
- Ghosh A, Saha AP, Saha S, Das A. Promoting the importance of recall visits among dental patients in India using a semiautonomous AI system. Stud Health Technol Inform 2022;16:85-92.
- Di Battista M, Kernitsky J, Dibart S. Artificial intelligence chatbots in patient communication: current possibilities. Int J Periodontics Restorative Dent 2024;44:731-8.
- Lyle DM. Implant maintenance: is there an ideal approach? Compend Contin Educ Dent 2013;34:386-90.
- Kracher CM, Smith WS. Oral health maintenance dental implants. Dent Assist 2010;79:27-35.
- Louropoulou A, Slot DE, Van der Weijden F. Mechanical self-performed oral hygiene of implant supported restorations: a systematic review. J Evid Based Dent Pract 2014;14:60-9.
- Carra MC, Blanc-Sylvestre N, Courtet A, Bouchard P. Primordial and primary prevention of peri-implant diseases: A systematic review and meta-analysis. J Clin Periodontol 2023;50:77-112.
- Banerjee, TN, Paul P, Debnath A, Banerjee S. Unveiling the prospects and challenges of artificial intelligence in implant dentistry. A systematic review. J Osseointegration 2024; 16: 53-60.
- Shehab AA, Shedd KE, Alamah W, Mardini S, Bite U, Gibreel W. Bridging gaps in health literacy for cleft lip and palate: The role of artificial intelligence and interactive educational materials. The Cleft Palate Craniofacial J 2024;9:1-7.
- Reading K, Knowles L, Towns S. The hygienist’s role in the management of the implant patient in primary care. Prim Dent J 2024;3:53-62.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Protez |
| Bölüm | Araştırma Makalesi |
| Yazarlar | |
| Yayımlanma Tarihi | 26 Mayıs 2025 |
| Gönderilme Tarihi | 28 Kasım 2024 |
| Kabul Tarihi | 16 Ocak 2025 |
| Yayımlandığı Sayı | Yıl 2025 Cilt: 14 Sayı: 2 |
