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  11. The Evaluation Of Tooth Whitening From A Perspective Of Artificial Intelligence: A Comparative Analytical Study

The evaluation of tooth whitening from a perspective of artificial intelligence: a comparative analytical study

Alaa Al-Haddad1, Mikel Alrabadi1, Othman Saadeh1

  • 1School of Dentistry, The University of Jordan, Amman, Jordan.

Frontiers in Digital Health
|December 10, 2025

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View abstract on PubMed

Summary
This summary is machine-generated.

Artificial intelligence chatbots provide useful tooth whitening information but are too complex for patients. Future AI must simplify language for better health literacy and patient education.

Area of Science:

  • Dental Aesthetics
  • Artificial Intelligence in Dentistry
  • Health Informatics

Background:

  • Artificial intelligence (AI) chatbots are increasingly used for dental aesthetics information.
  • Patients frequently consult AI for guidance on dental procedures like tooth whitening.

Purpose of the Study:

  • To evaluate the performance of multiple large language models (LLMs) in answering patient questions about tooth whitening.
  • To assess the usefulness, quality, reliability, and readability of AI-generated responses.

Main Methods:

  • 109 patient-derived questions on tooth whitening were submitted to four LLMs: ChatGPT-4o, Google Gemini, DeepSeek R1, and DentalGPT.
  • Responses were evaluated by two calibrated specialists using the Global Quality Scale (GQS) and the CLEAR tool.
  • Readability was assessed using the Flesch-Kincaid Reading Ease (FRE) and SMOG index.
Keywords:
AIcosmetic dentistrydental bleachinglarge language models

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Main Results:

  • LLMs generated high-quality, useful (68% "very useful"), and reliable information on tooth whitening.
  • No significant differences in quality or reliability were found between models or clinical domains.
  • Readability was a limitation, with a mean FRE score of 36.3 (difficult) and SMOG index of 11.0, requiring a high school reading level.

Conclusions:

  • Current LLMs offer valuable and dependable information regarding tooth whitening.
  • The reading level of AI responses is often too complex for average patient health literacy.
  • Future AI development should focus on simplifying language to enhance patient understanding and educational effectiveness.
patient education
tooth whitening