NCT07732985

Brief Summary

This prospective, blinded diagnostic accuracy study aims to compare the performance of three large language models-ChatGPT (GPT-5.5 Pro), Gemini 3.1 Pro, and Claude Opus 4.7-in endodontic diagnosis and case difficulty assessment. The models will be evaluated against expert consensus as the reference standard using standardized clinical data and periapical radiographs. Diagnostic accuracy, sensitivity, specificity, and agreement with expert consensus will be assessed to determine the potential of LLMs as clinical decision-support tools in endodontics.

Trial Health

65
Monitor

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
342

participants targeted

Target at P75+ for all trials

Timeline
4mo left

Started Sep 2026

Shorter than P25 for all trials

Status
not yet recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

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Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

July 10, 2026

Completed
19 days until next milestone

First Posted

Study publicly available on registry

July 29, 2026

Completed
1 month until next milestone

Study Start

First participant enrolled

September 1, 2026

Expected
3 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

December 1, 2026

1 month until next milestone

Study Completion

Last participant's last visit for all outcomes

January 1, 2027

Last Updated

July 29, 2026

Status Verified

July 1, 2026

Enrollment Period

3 months

First QC Date

July 10, 2026

Last Update Submit

July 23, 2026

Conditions

Outcome Measures

Primary Outcomes (1)

  • Diagnostic accuracy of ChatGPT (GPT-5.5 Pro), Gemini 3.1 Pro, and Claude Opus 4.7 for pulpal and periapical diagnosis

    Diagnostic performance of each large language model compared with the expert consensus reference standard. Accuracy, sensitivity, specificity, and agreement (Cohen's kappa) will be calculated according to the American Association of Endodontists (AAE) diagnostic criteria

    At baseline

Secondary Outcomes (1)

  • Accuracy of ChatGPT (GPT-5.5 Pro), Gemini 3.1 Pro, and Claude Opus 4.7 in endodontic case difficulty assessment

    At baseline

Interventions

Large language model used to analyze standardized clinical information and periapical radiographs to provide pulpal and periapical diagnosis and endodontic case difficulty assessment according to AAE criteria

Eligibility Criteria

Age16 Years+
Sexall
Healthy VolunteersYes
Age GroupsChild (0-17), Adult (18-64), Older Adult (65+)
Sampling MethodProbability Sample
Study Population

Systemically healthy adult patients (≥16 years) requiring primary endodontic treatment or retreatment at the Endodontic Department, Faculty of Dentistry, Cairo University, who provide informed consent.

You may qualify if:

  • Age above 16 years old.
  • Systemically healthy patient (ASA I or II).
  • Requiring endodontic treatment or retreatment
  • Patient's acceptance to participate in the study

You may not qualify if:

  • Medically compromised patients.
  • Pregnant women.
  • Traumatic dental injuries
  • Low quality periapical radiograph

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Central Study Contacts

Study Design

Study Type
observational
Observational Model
OTHER
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
PhD Candidate

Study Record Dates

First Submitted

July 10, 2026

First Posted

July 29, 2026

Study Start (Estimated)

September 1, 2026

Primary Completion (Estimated)

December 1, 2026

Study Completion (Estimated)

January 1, 2027

Last Updated

July 29, 2026

Record last verified: 2026-07