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NCT Number: NCT07706894

Diagnostic Accuracy of Educated Large Language Models in Endodontic Diagnosis and Case Difficulty Assessment

This diagnostic test accuracy (DTA) study aims to evaluate the diagnostic performance of educated large language models (Educated ChatGPT (GPT-5.5 Pro), Educated Gemini 3.1 Pro, and Educated Claude Opus 4.7) in endodontic practice. Their ability to establish pulpal and periapical diagnoses and assess endodontic case difficulty will be compared with the reference standard established by a panel of endodontic experts. Clinical and radiographic information from patients presenting for primary endodontic treatment or nonsurgical endodontic retreatment will be provided to both the AI models and the expert panel. The primary outcomes are the sensitivity, specificity, and the overall accuracy of the educated LLMs, with the objective of determining their potential role as reliable decision-support tools in endodontic diagnosis and treatment planning.

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Key information

Conditions

Pulpal and Periapical Diseases Jaw Diseases Mouth Diseases Periapical Diseases Periodontal Diseases Stomatognathic Diseases

Age range

16 year and older

Sex eligibility

All sexes

Study type

Observational

Who can participate

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age above 16 years old.
  • Requiring primary endodontic treatment or retreatment.
  • Availability of complete clinical examination records.
  • Availability of diagnostic radiographs.
  • Restorable teeth.
  • Patient's acceptance to participate in the study.

Exclusion criteria

  • Incomplete records
  • Pregnant women.
  • No restorability: Hopeless tooth.
  • Traumatic dental injuries
  • Periapical radiographic images of sub-optimal quality or artifacts/high scatter interfering with proper assessment.

Treatment and study plan

ChatGPT, Gemini, Calude

Diagnostic Test

Three educated large language models (LLMs) will be evaluated in this study: Educated ChatGPT (GPT-5.5 Pro, OpenAI), Educated Gemini 3.1 Pro (Google), and Educated Claude Opus 4.7 (Anthropic).

Primary outcomes

  1. Endodontic diagnosis according to AAE

    Time frame: baseline

    Pulpal and periapical diagnosis

Secondary outcomes

  1. Difficulty assessment according to AAE

    Time frame: baseline

Sponsors and collaborators

Lead sponsor

Cairo University

Other

Registry information

Official study title

Accuracy of Educated Large Language Models Compared With Endodontic Experts in the Diagnosis and Difficulty Assessment of Endodontic Cases: A Diagnostic Test Accuracy Study

Important dates

Study start
2026
Primary completion
2026
Study completion
2027
First posted
Jul 16, 2026
Registry last updated
Jul 16, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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