Diagnostic Accuracy of Educated Large Language Models in Endodontic Diagnosis and Case Difficulty Assessment
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: ChatGPT, Gemini, Calude.
- Who it may be relevant to
- Registry conditions: Pulpal and Periapical Diseases. Basic parameters: from 16 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official 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
Overview
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.
Interventions
- Diagnostic test ChatGPT, Gemini, Calude
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 outcome measures
- Endodontic diagnosis according to AAE [Time frame: baseline]
Secondary outcome measures (1)
- Difficulty assessment according to AAE [Time frame: baseline]
Eligibility criteria
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.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Study design
- Observational model
- Other
Study locations
Center list to be confirmed — check the primary protocol.
Identifiers
NCT: NCT07706894 · new endo (7.1.1)