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Artificial intelligence chatbots in endodontic education-Concepts and potential applications.

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Artificial intelligence (AI) chatbots offer personalized learning and clinical decision support in endodontic education. However, challenges like misinformation and bias require careful integration and validation of these AI tools.

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Area of Science:

  • Dental Education
  • Artificial Intelligence in Medicine
  • Endodontics

Background:

  • Artificial intelligence (AI) is transforming education, with AI chatbots showing potential in specialized fields like dentistry.
  • Endodontic education faces knowledge gaps regarding AI chatbot capabilities and limitations, hindering effective adoption.
  • Understanding AI chatbot functionalities (NLP, ML, DL) is crucial for their application in specialized learning environments.

Purpose of the Study:

  • To explain AI chatbot functionalities, including natural language processing (NLP), machine learning (ML), and deep learning (DL).
  • To explore AI chatbot applications in endodontic education for personalized learning, interactive training, and clinical decision support.
  • To discuss challenges associated with AI chatbots, such as technical limitations, ethical concerns, and misinformation.

Main Methods:

  • This narrative review synthesizes current literature on AI chatbots and their role in endodontic education.
  • The review analyzes the core technologies underpinning AI chatbots.
  • It examines reported benefits and challenges of AI chatbot integration in educational settings.

Main Results:

  • AI chatbots provide immediate knowledge access, personalized learning experiences, and clinical reasoning development through case-based scenarios.
  • Educators can benefit from streamlined curriculum development, automated assessments, and integrated evidence-based resources.
  • Concerns include chatbot inaccuracies (hallucinations), algorithmic bias, plagiarism risks, and the potential for spreading misinformation.

Conclusions:

  • AI chatbots offer significant potential to enhance endodontic education, but their effective integration requires addressing technical and ethical challenges.
  • Limited endodontic-specific research necessitates the development and validation of tailored AI chatbot solutions.
  • Collaborative efforts are essential for ethical implementation, accurate content, and robust evaluation frameworks for AI in endodontics.