[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100643564":3},{"organization":4,"armGroups":7,"interventions":8,"overallOfficials":12,"centralContacts":23,"locations":7,"responsibleParty":29,"collaborators":7,"id":33,"slug":34,"hasResults":35,"nctId":36,"briefTitle":37,"officialTitle":38,"acronym":7,"eligibilityCriteria":39,"healthyVolunteers":35,"sex":40,"minAge":41,"maxAge":42,"enrollmentInfo":43,"targetDuration":46,"studyType":47,"phases":7,"briefSummary":48,"conditions":49,"keywords":51,"overallStatus":59,"whyStopped":7,"lastUpdateSubmitDate":60,"lastUpdatePostDateStruct":61,"startDateStruct":64,"completionDateStruct":66,"leadSponsor":68,"locationsCount":7},{"fullName":5,"class":6},"Cairo University","OTHER",null,[9],{"type":6,"name":10,"description":11,"armGroupLabels":7,"otherNames":7},"Artificial Intelligence models (YOLO and MASK-RCNN)","Machine learning model well be used for assessment of intraoral photographs for the detection, identification, and scoring of white spot lesions in teeth",[13,17,20],{"name":14,"affiliation":15,"role":16},"Asmaa A. Mohamed Yassen","Professor of Conservative Dentistry Department, Faculty of Dentistry, Cairo University","STUDY_DIRECTOR",{"name":18,"affiliation":19,"role":16},"Rawda Hesham Abdelaziz","Associate Professor of Conservative Dentistry Department, Faculty of Dentistry, Cairo University",{"name":21,"affiliation":22,"role":16},"Asmaa A. Elsayed Osman","Lecturer of Information Technology, Faculty of Computers and Artificial Intelligence, Cairo University",[24],{"name":25,"role":26,"phone":27,"phoneExt":7,"email":28},"Mohamed Hisham A.ELFattah Gabr, PhD","CONTACT","+201005660842","mohamed_gabr@dentistry.cu.edu.eg",{"type":30,"investigatorFullName":31,"investigatorTitle":32,"investigatorAffiliation":5,"oldNameTitle":7,"oldOrganization":7},"PRINCIPAL_INVESTIGATOR","Mohamed Hisham Abd ElFattah Gabr Ali","Principal Investigator","100643564","artificial-intelligence-versus-clinical-examination-in-white-spot-lesions-detection-identification-and-scoring-100643564",false,"NCT07639749","Artificial Intelligence Versus Clinical Examination in White Spot Lesions Detection, Identification, And Scoring","Diagnostic Accuracy of Artificial Intelligence Analysis Using Intraoral Photographs Versus Clinical Examination in White Spot Lesions Detection, Identification, And Scoring.","Inclusion Criteria:\n\n1. Adult patients aged 20 - 60 years\n2. Males or Females\n3. Patients with white spot lesions of teeth 4 - Co-operative patients with interest in participation in the study\n\nExclusion Criteria:\n\n1. Patients with orthodontic appliances or bridgework that might interfere with evaluation and assessment\n2. Patients with no white spot lesions\n3. Patients with systematic diseases that might affect participation\n4. Patients refusing to sign the informed consent or not willing to be part of the study","ALL","20 Years","60 Years",{"count":44,"type":45},329,"ESTIMATED","1 Year","OBSERVATIONAL","The goal of this observational study is to compare the diagnostic accuracy of Clinical examination as a standard for detection, identification and scoring of White Spot Lesions Versus Artificial intelligence analysis of intraoral photographs. The photographs are examined by experienced dental professionals to maintain diagnostic accuracy. Machine learning models YOLO and Mask-RCNN will analyze these images in three phases: pre-analytical, analytical and post-analytical. A dataset of 329 labelled photographs, annotated by experts, is used to train these models. Data augmentation methods enhance model performance, and accuracy is assessed against clinical examination results to confirm reliability.\n\nThe main question it aims to answer is:\n\n\\- Is artificial intelligence analysis of intraoral photographs as accurate as clinical assessment in the detection, identification, and scoring of white spot lesions among adult Egyptian patients attending Cairo University Dental Hospital?",[50],"White Spot Lesion of Tooth",[52,53,54,55,56,57,58],"white spot lesions","dental","caries","intraoral","photography","diagnostic accuracy","artificial intelligence","NOT_YET_RECRUITING","2026-06-08",{"date":62,"type":63},"2026-06-10","ACTUAL",{"date":65,"type":45},"2026-07-01",{"date":67,"type":45},"2027-11-01",{"name":5,"class":6}]