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Assessment of the Mouth01:26

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A thorough mouth assessment, including inspection and palpation of the lips, gums, tongue, tonsils, uvula, and pharynx, is crucial in detecting potential health issues. Diseases ranging from oral cancer to systemic conditions like diabetes could be identified early through careful oral examination. This article provides a detailed guide on conducting a comprehensive mouth assessment.
Mouth Inspection
The inspection begins with visually examining the mouth for symmetry, color, and size.
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Author Spotlight: 3D Movement Assessment of Maxillary Posterior Teeth in Clear Aligner Treatment
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Reliability and Performance of Four Large Language Models in Orthodontic Knowledge Assessment.

Shankargouda Patil1, Gabriel Eisenhuth1, Tarek El-Bialy2

  • 1College of Dental Medicine, Roseman University of Health Sciences, South Jordan, Utah, USA.

Journal of Dental Education
|July 27, 2025
PubMed
Summary
This summary is machine-generated.

This study assessed artificial intelligence (AI) large language models (LLMs) for orthodontic education. While Microsoft CoPilot showed reliability and ChatGPT-4.0 accuracy, AI responses remain inconsistent for standalone use.

Keywords:
LLMNBDEartificial intelligenceknowledge assessmentorthodonticsstudents

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Area of Science:

  • Dental Education
  • Artificial Intelligence in Medicine

Background:

  • Large language models (LLMs) are increasingly used as educational resources.
  • Assessing the performance of AI in specialized fields like orthodontics is crucial.

Purpose of the Study:

  • To evaluate the accuracy and reliability of popular LLMs in answering orthodontic board examination questions.
  • To determine the consistency of AI responses across multiple trials.

Main Methods:

  • Four LLMs (ChatGPT 4.0, ChatGPT 4o, Google Gemini, Microsoft CoPilot) were tested.
  • Orthodontic questions from the National Board of Dental Examiners examinations were used.
  • Response consistency was assessed over three trials, with reliability analyzed using Cohen's and Fleiss' Kappa.

Main Results:

  • Microsoft CoPilot exhibited the highest reliability, while ChatGPT-4.0 demonstrated the highest accuracy.
  • Significant variability in responses across trials indicated AI inconsistency.
  • Older AI models sometimes outperformed newer versions, and updates did not guarantee improved reliability.

Conclusions:

  • Current LLMs exhibit inconsistent performance, limiting their use as standalone tools in orthodontic education.
  • AI models show potential as supplementary study aids but require further refinement for educational deployment.