[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100574501":3},{"organization":4,"armGroups":7,"interventions":17,"overallOfficials":23,"centralContacts":26,"locations":36,"responsibleParty":55,"collaborators":10,"id":58,"slug":59,"hasResults":60,"nctId":61,"briefTitle":62,"officialTitle":63,"acronym":10,"eligibilityCriteria":64,"healthyVolunteers":60,"sex":65,"minAge":66,"maxAge":67,"enrollmentInfo":68,"targetDuration":10,"studyType":71,"phases":10,"briefSummary":72,"conditions":73,"keywords":10,"overallStatus":75,"whyStopped":10,"lastUpdateSubmitDate":76,"lastUpdatePostDateStruct":77,"startDateStruct":80,"completionDateStruct":82,"leadSponsor":84,"locationsCount":85},{"fullName":5,"class":6},"Cairo University","OTHER",[8,12],{"label":9,"type":10,"description":11,"interventionNames":10},"intraoral images for Children with Dental Plaque for assessment by dentist",null,"Intervention Overview: Participants will undergo intraoral imaging using \\[intraoral camera\\].\n\nIntervention Overview: A trained dentist or dental hygienist will conduct a clinical assessment of each child's dental plaque levels using standard clinical criteria.\n\nAssessment Method: The clinical assessment will involve visual inspection and may use plaque index to evaluate the amount of plaque present.\n\nData Collection and Analysis:\n\nOutcome Measures: The results from the AI models and clinical assessments will be compared to calculate diagnostic accuracy metrics, such as sensitivity, specificity, positive predictive value, and negative predictive value.",{"label":13,"type":10,"description":14,"interventionNames":15},"intraoral images for Children with Dental Plaque for assessment by AI models","Intervention Overview: Participants will undergo intraoral imaging using \\[intraoral camera\\].\n\nAI Models: The images will be analyzed using different AI models designed for dental plaque detection.\n\nData Collection and Analysis:\n\nOutcome Measures: The results from the AI models and clinical assessments will be compared to calculate diagnostic accuracy metrics, such as sensitivity, specificity, positive predictive value, and negative predictive value.",[16],"Diagnostic Test: Dental Plaque Detection Using AI Models",[18],{"type":19,"name":20,"description":21,"armGroupLabels":22,"otherNames":10},"DIAGNOSTIC_TEST","Dental Plaque Detection Using AI Models","1. AI Model Analysis:\n\n   Description: Intraoral images of participants will be captured using standardized imaging techniques. These images will then be analyzed using various artificial intelligence models specifically designed for detecting dental plaque. The AI models will process the images to identify and quantify the presence of dental plaque.\n2. Clinical Assessment:\n\nDescription: A qualified dentist will perform a traditional clinical examination of the participants to assess dental plaque using standard examination techniques. This will serve as the reference standard against which the AI models will be compared.\n\nStudy Procedures Image Acquisition: Intraoral images will be taken of each participant using \\[ intraoral camera\\].\n\nAI Model Evaluation: The captured images will be analyzed using different AI algorithms, which may include.",[13],[24],{"name":5,"affiliation":5,"role":25},"STUDY_DIRECTOR",[27,32],{"name":28,"role":29,"phone":30,"phoneExt":10,"email":31},"Naema Altrablsi","CONTACT","00201152442411","naema.altrablsi@dentistry.cu.edu.eg",{"name":33,"role":29,"phone":34,"phoneExt":10,"email":35},"Hala Mohiey Eldin, Prof. Doctor","00201001459467","hala.mohyeldin@dentistry.cu.edu.eg",[37],{"facility":5,"status":10,"city":38,"state":10,"zip":39,"country":40,"countryCode":41,"cosmosGeoPoint":42,"geoPoint":47,"contacts":48},"Cairo","11511","Egypt","EG",{"type":43,"coordinates":44},"Point",[45,46],31.24967,30.06263,{"lat":46,"lon":45},[49,52],{"name":50,"role":29,"phone":51,"phoneExt":10,"email":31},"cairo universitty","0020238355275",{"name":53,"role":54,"phone":10,"phoneExt":10,"email":10},"Naema Ahmed","PRINCIPAL_INVESTIGATOR",{"type":56,"investigatorFullName":53,"investigatorTitle":57,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"SPONSOR_INVESTIGATOR","naemaahmed","100574501","comparative-accuracy-of-ai-models-and-clinical-assessment-for-dental-plaque-detection-in-children-100574501",false,"NCT06760104","Comparative Accuracy of AI Models and Clinical Assessment for Dental Plaque Detection in Children","Accuracy of Dental Plaque Detection From Intraoral Images Using Different Artificial Intelligence Models Versus Clinical Assessment Among a Group of Children: A Diagnostic Accuracy Study.","Inclusion Criteria:\n\n.Study participants: Children within age range (7-12) years old. .Teeth without metal crowns or amalgam restoration.\n\nExclusion Criteria:\n\n* Children with developmental enamel defects\n* Children who are unwilling to cooperate or who has mental retardation and are prohibited from having their images taken. .Children who's their legal guardians will not approve to participate in the study.","ALL","7 Years","12 Years",{"count":69,"type":70},323,"ESTIMATED","OBSERVATIONAL","This diagnostic accuracy study aims to evaluate the effectiveness of various artificial intelligence models in detecting dental plaque from intraoral images compared to clinical assessments performed by dentists among children. The study seeks to determine the accuracy, sensitivity, specificity, and overall performance of AI technologies in identifying dental plaque. study study Design: Observational study",[74],"Dental Plaque","NOT_YET_RECRUITING","2025-01-03",{"date":78,"type":79},"2025-01-06","ACTUAL",{"date":81,"type":70},"2025-01-01",{"date":83,"type":70},"2025-12-30",{"name":53,"class":6},1]