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Artificial Intelligence Evaluation of Fillings

NCT06022731 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 4323

Last updated 2023-09-05

No results posted yet for this study

Summary

The goal of this Non-Interventional Clinical Research is to detect the prevalence and distribution of filling and overhanging filling without the need for additional bitewing radiographs using panoramic images, based on a deep CNN (Convolutional Neural Network) architecture trained through supervised learning.

In this study, retrospectively obtained radiographs were used in the development of artificial intelligence models for relevant situations. These datasets were obtained from the images of the patients who applied to ESOGU (Eskişehir Osmangazi University) Dentistry Faculty, Dentomaxillofacial Radiology clinic for various dental purposes. Eskisehir Osmangazi University Non-Interventional Clinical Research Ethics Board (decision date and decision number: 04.10.2022/22) approved the study protocol. The principles of the Helsinki Declaration were followed in the study.

Conditions

  • Dentomaxillofacial Radiology

Interventions

DIAGNOSTIC_TEST

Panoramic Radiography

this retrospective study includes analysis of radiographs previously taken from patients for various purposes

Sponsors & Collaborators

  • Eskisehir Osmangazi University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-01-01
Primary Completion
2023-01-01
Completion
2023-03-01

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 NCT06022731 on ClinicalTrials.gov