International Dental Journal, Journal Year: 2024, Volume and Issue: 74(6), P. 1470 - 1470
Published: Sept. 25, 2024
Language: Английский
International Dental Journal, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 1, 2025
In the final part of this two article on artificial intelligence (AI) in dentistry we review its transformative role, focusing AI dental education, patient communications, challenges integration, strategies to overcome barriers, ethical considerations, and finally, recently released International Dental Federation (FDI) Communique (white paper) Dentistry. education is highlighted for potential enhancing theoretical practical dimensions, including telemonitoring virtual training ecosystems. Challenges integration are outlined, such as data availability, bias, human accountability. Strategies these include promoting literacy, establishing regulations, specific implementations. Ethical considerations within dentistry, privacy algorithm emphasized. The need clear guidelines ongoing evaluation systems crucial. FDI White Paper Dentistry provides insights into significance oral care, research, along with standards governance. It discusses AI's impact individual patients, community health, research. paper addresses biases, limited generalizability, accessibility, regulatory requirements practice. conclusion, plays a significant role modern offering benefits diagnosis, treatment planning, decision-making. While facing challenges, strategic initiatives targeted implementations can help barriers maximize dentistry. essential ensuring responsible, effective efficacious deployment technologies ecosystem.
Language: Английский
Citations
1
International Dental Journal, Journal Year: 2025, Volume and Issue: 75(3), P. 1564 - 1565
Published: March 23, 2025
Language: Английский
Citations
0
International Endodontic Journal, Journal Year: 2025, Volume and Issue: unknown
Published: March 31, 2025
Abstract The integration of artificial intelligence (AI) into education is transforming learning across various domains, including dentistry. Endodontic can significantly benefit from AI chatbots; however, knowledge gaps regarding their potential and limitations hinder effective utilization. This narrative review aims to: (A) explain the core functionalities chatbots, reliance on natural language processing (NLP), machine (ML), deep (DL); (B) explore applications in endodontic for personalized learning, interactive training, clinical decision support; (C) discuss challenges posed by technical limitations, ethical considerations, misinformation. highlights that chatbots provide learners with immediate access to knowledge, educational experiences, tools developing reasoning through case‐based learning. Educators streamlined curriculum development, automated assessment creation, evidence‐based resource integration. Despite these advantages, concerns such as chatbot hallucinations, algorithmic biases, plagiarism, spread misinformation require careful consideration. Analysis current research reveals limited endodontic‐specific studies, emphasizing need tailored solutions validated accuracy relevance. Successful will collaborative efforts among educators, developers, professional organizations address challenges, ensure use, establish evaluation frameworks.
Language: Английский
Citations
0
Frontiers in Oral Health, Journal Year: 2025, Volume and Issue: 6
Published: April 7, 2025
Patients frequently seek dental information online, and generative pre-trained transformers (GPTs) may be a valuable resource. However, the quality of responses based on varying prompt designs has not been evaluated. As implant treatment is widely performed, this study aimed to investigate influence design GPT performance in answering commonly asked questions related implants. Thirty about dentistry - covering patient selection, associated risks, peri-implant disease symptoms, for missing teeth, prevention, prognosis were posed four different models with designs. Responses recorded independently appraised by two periodontists across six domains. All performed well, classified as good quality. The contextualized model worse treatment-related (21.5 ± 3.4, p < 0.05), but outperformed input-output, zero-shot chain thought, instruction-tuned citing appropriate sources its (4.1 1.0, 0.001). had less clarity relevance compared other models. GPTs can provide accurate, complete, useful While enhance response quality, further refinement necessary optimize performance.
Language: Английский
Citations
0
International Dental Journal, Journal Year: 2024, Volume and Issue: 74(6), P. 1470 - 1470
Published: Sept. 25, 2024
Language: Английский
Citations
0