Clinical trial Recruiting at 1 site Observational Ages 18 and up

Large language models for turning structured dental radiology data into narrative reports

Official title: Evaluation of Large Language Models for Transforming Structured Dental Radiology Data Into Narrative Radiology Reports

Run by Hospital of the Ministry of Interior, Kielce, Poland · NCT07676318 · Data updated 2026-11-12

This study tests whether a language model can convert organized dental X‑ray findings into clear, complete radiology reports.

Quick facts

Study typeObservational
Ages18 Years and up
SexAll
Enrollment100 (estimated)
SponsorHospital of the Ministry of Interior, Kielce, Poland
Academic / other
Locations1 site (Kielce, Świętokrzyskie Voivodeship)
StatusRecruiting
StartedJanuary 1, 2026
Main results expectedNovember 2026
Study endsDecember 2026
Registry record updatedSeptember 22, 2026
Trial IDNCT07676318 on ClinicalTrials.gov

Is this trial a fit for you?

Likely a good fit

Dental radiology records from patients with permanent dentition after exfoliation, with structured radiology data suitable for report generation.

Probably not a fit

Patients whose records lack complete or reliable structured input data may not benefit from improved reporting.

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This observational study evaluates the use of large language models to generate narrative dental radiology reports from structured input such as charts or diagrams. It focuses on the quality, clarity, and clinical usefulness of the reports, comparing model-generated outputs with traditionally prepared reports. The project examines how prompt design and model settings influence report quality, aiming to identify configurations that improve completeness and factual accuracy without interpreting images or making diagnoses. Data are restricted to structured radiology findings and do not involve autonomous diagnostic decisions. The research will assess reliability, terminology, readability, and alignment with source data across multiple configurations.

Why it matters

Potential benefit: If successful, clinicians may gain faster, consistent radiology reporting from structured data while preserving accuracy and readability.

How similar studies have gone: Prior work in other medical domains suggests language-model-assisted report generation can improve efficiency and consistency, though dental-specific validation is ongoing.

Who can join: the full rules

Show full inclusion / exclusion criteria
Inclusion Criteria:

* Dental radiology records based on dental X-ray examination performed on the basis of a written referral from a dentist or physician
* Dental X-ray examinations performed for screening, diagnostic, or treatment-planning purposes
* Records from patients with permanent dentition after completion of exfoliation

Exclusion Criteria:

* Records from patients with mixed dentition before completion of exfoliation
* Records with incomplete, ambiguous, or internally inconsistent structured dental radiology data preventing reliable report generation
* Records with missing information required for evaluation of the generated report
* Duplicate records from the same radiographic examination
* Records in which anonymization or pseudonymization cannot be ensured

Where it's running

  • Department of Maxillofacial Surgery
    Kielce, Świętokrzyskie Voivodeship, Poland
    Recruiting

Study contacts

Similar studies

Other studies for the same condition or treatment. Recruiting studies are listed first.

How to take part

  1. Review the eligibility criteria above with your treating physician.
  2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
  3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.