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LLM Performance in Endodontic Diagnostics

NCT07281066 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 120

Last updated 2025-12-15

No results posted yet for this study

Summary

The goal of this prospective observational study is to evaluate the ability of three large language models (ChatGPT-4o, Gemini Advanced, and Claude 3.7) to support diagnosis and treatment decision-making in adult patients presenting with common endodontic conditions.

The main questions the study aims to answer are:

Can LLMs accurately determine the endodontic diagnosis when provided with structured clinical information and periapical radiographs?

Can LLMs propose appropriate treatment plans comparable to decisions made by endodontic specialists?

To answer these questions, researchers will compare the diagnostic and treatment accuracy of three AI models using a consensus diagnosis from endodontic specialists as the reference standard.

Participants will:

Receive routine endodontic examination and periapical radiographs as part of standard clinical care.

Have their anonymized clinical histories and radiographs entered into the three AI models.

Not interact directly with any AI system; all evaluations will be performed by the research team.

This study aims to understand how large language models perform under real-world clinical conditions and whether these systems may play a supportive role in endodontic diagnostics in the future.

Conditions

  • Endodontic Diagnosis, Endodontic Diseases, Endodontic Treatment, Endodontic Decision-making

Interventions

DIAGNOSTIC_TEST

AI-Based Diagnostic Assessment

Participants' anonymized clinical information, including structured patient history and periapical radiographs, was used as input for three large language models (ChatGPT-4o, Gemini Advanced, Claude 3.7). The models were asked to determine the endodontic diagnosis and propose an appropriate treatment plan. No treatment, device, or drug was administered to participants. The intervention consists solely of AI-based interpretation of pre-existing clinical data.

Sponsors & Collaborators

  • Marmara University

    lead OTHER

Principal Investigators

  • ayşe karadayı, asst. prof. · marmara university faculty of dentistry

Eligibility

Min Age
18 Years
Max Age
65 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-07-07
Primary Completion
2025-08-05
Completion
2025-10-03

Countries

  • Turkey (Türkiye)

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07281066 on ClinicalTrials.gov