[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"accuracy-of-artificial-intelligence-in-fixed-dental-prosthesis-design\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:accuracy-of-artificial-intelligence-in-fixed-dental-prosthesis-design":27},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,1,0,[8],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":18,"enrollmentInfo":19,"targetDuration":4,"studyType":22,"phases":23,"briefSummary":25,"conditions":26,"keywords":28,"overallStatus":37,"whyStopped":4,"lastUpdateSubmitDate":38,"lastUpdatePostDateStruct":39,"startDateStruct":42,"completionDateStruct":44,"leadSponsor":46,"locationsCount":5},"100626171","artificial-intelligence-versus-conventional-digital-design-for-fixed-dental-prosthesis-100626171",false,"NCT07432165","Artificial Intelligence Versus Conventional Digital Design for Fixed Dental Prosthesis","Accuracy Assessment of Artificial Intelligence Versus Conventional Digital Design for Fixed Dental Prosthesis: (An Invitro Study)","Inclusion Criteria:\n\n* Adults aged 18-65 years Patients with a damaged tooth requiring a fixed dental prosthesis Available digital intraoral scans Adequate occlusal anatomy for analysis of opposing teeth\n\nExclusion Criteria:\n\n* Incomplete or poor-quality digital scans Severe occlusal abnormalities affecting analysis Patients outside the specified age range","ALL","18 Years","65 Years",{"count":20,"type":21},1000,"ESTIMATED","INTERVENTIONAL",[24],"NA","This in vitro study aims to evaluate the accuracy of an Artificial Intelligence (AI)-based automatic design system for fixed dental prosthesis (FDP) compared with conventional computer-aided design (CAD) software. Digital scans of teeth requiring fixed dental prosthesis will be collected and used to generate prosthetic designs using two approaches: human-designed CAD restorations and AI-generated restorations.\n\nThe primary outcome is design accuracy assessed using 3D superimposition and Intersection over Union (IOU) percentage. Secondary outcomes include margin detection performance measured using F1 score, precision, and recall. A total sample size of 438 scans will be analyzed.\n\nThe study will determine whether AI-generated prosthesis designs demonstrate comparable accuracy to conventional digital designs.",[27],"Accuracy of Artificial Intelligence in Fixed Dental Prosthesis Design",[29,30,31,32,33,34,35,36],"Artificial Intelligence","CAD\u002FCAM","Fixed Dental Prosthesis","Dental Crown Design","3D Superimposition","Deep Learning","Generative Adversarial Network (GAN)","Prosthodontics","RECRUITING","2026-02-19",{"date":40,"type":41},"2026-02-25","ACTUAL",{"date":43,"type":41},"2025-06-15",{"date":45,"type":21},"2026-06-17",{"name":47,"class":48},"October University for Modern Sciences and Arts","OTHER"]