xml: <clinical_study>
    <!-- This xml conforms to an XML Schema at:
      https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
    <required_header>
      <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
      <link_text>Link to the current ClinicalTrials.gov record.</link_text>
      <url>https://clinicaltrials.gov/ct2/show/NCT06022731</url>
    </required_header>
    <id_info>
      <org_study_id>Retrospective</org_study_id>
      <nct_id>NCT06022731</nct_id>
    </id_info>
    <brief_title>Artificial Intelligence Evaluation of Fillings</brief_title>
    <official_title>A Yolo-V5 Approaches to Evaluation of Filling and Overhanging Filling: An Artificial Intelligence Study</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Eskisehir Osmangazi University</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>Eskisehir Osmangazi University</source>
    <oversight_info>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
      <is_fda_regulated_device>No</is_fda_regulated_device>
    </oversight_info>
    <brief_summary>
      <textblock>
        The goal of this Non-Interventional Clinical Research is to detect the prevalence and&#xD;
        distribution of filling and overhanging filling without the need for additional bitewing&#xD;
        radiographs using panoramic images, based on a deep CNN (Convolutional Neural Network)&#xD;
        architecture trained through supervised learning.&#xD;
  &#xD;
        In this study, retrospectively obtained radiographs were used in the development of&#xD;
        artificial intelligence models for relevant situations. These datasets were obtained from the&#xD;
        images of the patients who applied to ESOGU (Eskişehir Osmangazi University) Dentistry&#xD;
        Faculty, Dentomaxillofacial Radiology clinic for various dental purposes. Eskisehir Osmangazi&#xD;
        University Non-Interventional Clinical Research Ethics Board (decision date and decision&#xD;
        number: 04.10.2022/22) approved the study protocol. The principles of the Helsinki&#xD;
        Declaration were followed in the study.&#xD;
      </textblock>
    </brief_summary>
    <overall_status>Completed</overall_status>
    <start_date type="Actual">January 1, 2022</start_date>
    <completion_date type="Actual">March 1, 2023</completion_date>
    <primary_completion_date type="Actual">January 1, 2023</primary_completion_date>
    <study_type>Observational</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <observational_model>Case-Only</observational_model>
      <time_perspective>Retrospective</time_perspective>
    </study_design_info>
    <primary_outcome>
      <measure>The success of artificial intelligence models for filling and overhanging filling</measure>
      <time_frame>1 year</time_frame>
      <description>It is obtained by calculating the sensitivity, precision, and F1 scores values for filling and overhanging filling.</description>
    </primary_outcome>
    <number_of_groups>2</number_of_groups>
    <enrollment type="Actual">4323</enrollment>
    <condition>Dentomaxillofacial Radiology</condition>
    <arm_group>
      <arm_group_label>Filling</arm_group_label>
    </arm_group>
    <arm_group>
      <arm_group_label>Overhanging Filling</arm_group_label>
    </arm_group>
    <intervention>
      <intervention_type>Diagnostic Test</intervention_type>
      <intervention_name>Panoramic Radiography</intervention_name>
      <description>this retrospective study includes analysis of radiographs previously taken from patients for various purposes</description>
      <arm_group_label>Filling</arm_group_label>
      <arm_group_label>Overhanging Filling</arm_group_label>
    </intervention>
    <eligibility>
      <study_pop>
        <textblock>
          These datasets were obtained from the images of the patients who applied to ESOGU Dentistry&#xD;
          Faculty, Dentomaxillofacial Radiology clinic for various dental purposes.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Images of individuals in the permanent dentition period&#xD;
  &#xD;
            -  Artifact-free images in the examination region&#xD;
  &#xD;
            -  Individuals with a history of restorative dental treatment&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Images of individuals in mixed dentition&#xD;
  &#xD;
            -  Radiographic images obtained by incorrect positioning of the patient or containing&#xD;
               artifacts&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>N/A</minimum_age>
      <maximum_age>N/A</maximum_age>
    </eligibility>
    <location>
      <facility>
        <name>Eskişehir Osmangazi University</name>
        <address>
          <city>Eskişehir</city>
          <zip>26200</zip>
          <country>Turkey</country>
        </address>
      </facility>
    </location>
    <location_countries>
      <country>Turkey</country>
    </location_countries>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>August 8, 2023</study_first_submitted>
    <study_first_submitted_qc>August 31, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">September 5, 2023</study_first_posted>
    <last_update_submitted>August 31, 2023</last_update_submitted>
    <last_update_submitted_qc>August 31, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">September 5, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Principal Investigator</responsible_party_type>
      <investigator_affiliation>Eskisehir Osmangazi University</investigator_affiliation>
      <investigator_full_name>Elif Bilgir</investigator_full_name>
      <investigator_title>Associated Professor</investigator_title>
    </responsible_party>
    <keyword>dental filling</keyword>
    <keyword>dentistry</keyword>
    <keyword>deep learning,</keyword>
    <patient_data>
      <sharing_ipd>Yes</sharing_ipd>
      <ipd_description>The investigators plan to publish the findings obtained as a result of the study in internationally journals and share this information within the publication.</ipd_description>
      <ipd_info_type>Study Protocol</ipd_info_type>
      <ipd_info_type>Statistical Analysis Plan (SAP)</ipd_info_type>
      <ipd_info_type>Clinical Study Report (CSR)</ipd_info_type>
    </patient_data>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: download date: ClinicalTrials.gov processed this data on September 20, 2023
  link text: Link to the current ClinicalTrials.gov record.
  url: https://clinicaltrials.gov/ct2/show/NCT06022731
  org study id: Retrospective
  nct id: NCT06022731
  lead sponsor: 
  is fda regulated drug: No
  is fda regulated device: No
  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.
  observational model: Case-Only
  time perspective: Retrospective
  measure: The success of artificial intelligence models for filling and overhanging filling
  time frame: 1 year
  description: It is obtained by calculating the sensitivity, precision, and F1 scores values for filling and overhanging filling.
  arm group label: Filling
  arm group label: Overhanging Filling
  intervention type: Diagnostic Test
  intervention name: Panoramic Radiography
  description: this retrospective study includes analysis of radiographs previously taken from patients for various purposes
  arm group label: Filling
  arm group label: Overhanging Filling
  study pop: 
  sampling method: Probability Sample
  criteria: 
  gender: All
  minimum age: N/A
  maximum age: N/A
  facility: 
  country: Turkey
  responsible party type: Principal Investigator
  investigator affiliation: Eskisehir Osmangazi University
  investigator full name: Elif Bilgir
  investigator title: Associated Professor
  sharing ipd: Yes
  ipd description: The investigators plan to publish the findings obtained as a result of the study in internationally journals and share this information within the publication.
  ipd info type: Study Protocol
  ipd info type: Statistical Analysis Plan (SAP)
  ipd info type: Clinical Study Report (CSR)