[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100532316":3},{"organization":4,"armGroups":7,"interventions":13,"overallOfficials":18,"centralContacts":22,"locations":28,"responsibleParty":42,"collaborators":10,"id":44,"slug":45,"hasResults":46,"nctId":47,"briefTitle":48,"officialTitle":49,"acronym":10,"eligibilityCriteria":50,"healthyVolunteers":46,"sex":51,"minAge":10,"maxAge":10,"enrollmentInfo":52,"targetDuration":10,"studyType":55,"phases":10,"briefSummary":56,"conditions":57,"keywords":10,"overallStatus":31,"whyStopped":10,"lastUpdateSubmitDate":61,"lastUpdatePostDateStruct":62,"startDateStruct":65,"completionDateStruct":67,"leadSponsor":69,"locationsCount":70},{"fullName":5,"class":6},"Tianjin Eye Hospital","OTHER",[8],{"label":9,"type":10,"description":10,"interventionNames":11},"Cornea diseases diagnosed by artificial intelligence algorithm",null,[12],"Diagnostic Test: Cornea diseases diagnosed by artificial intelligence algorithm",[14],{"type":15,"name":9,"description":16,"armGroupLabels":17,"otherNames":10},"DIAGNOSTIC_TEST","An artificial intelligence algorithm was applied to diagnose cornea diseases from slit-lamp images.",[9],[19],{"name":20,"affiliation":5,"role":21},"Yan Wang, Prof","STUDY_CHAIR",[23],{"name":24,"role":25,"phone":26,"phoneExt":10,"email":27},"Yan Huo, Master","CONTACT","13102118953","hy13102118953@163.com",[29],{"facility":30,"status":31,"city":32,"state":33,"zip":10,"country":34,"countryCode":35,"cosmosGeoPoint":36,"geoPoint":41,"contacts":10},"Tiajin Eye Hospital","RECRUITING","Tianjin","Tianjin Municipality","China","CN",{"type":37,"coordinates":38},"Point",[39,40],117.17667,39.14222,{"lat":40,"lon":39},{"type":43,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR","100532316","artificial-intelligence-for-screening-of-multiple-corneal-diseases-100532316",false,"NCT06211218","Artificial Intelligence for Screening of Multiple Corneal Diseases","Application of Deep Learning for Screening Multiple Corneal Diseases","Inclusion Criteria:\n\n1. The quality of slit-lamp images should clinical acceptable.\n2. More than 90% of the slit-lamp image area including three main regions (sclera, pupil, and lens) are easy to read and discriminate.\n\nExclusion Criteria:\n\n1）Insufficient information for diagnosis.","ALL",{"count":53,"type":54},3000,"ESTIMATED","OBSERVATIONAL","This study developed a deep learning algorithm based on anterior segment images and prospectively validated its ability to identify corneal diseases.The effectiveness and accuracy of this algorithm was evaluated by sensitivity, specificity, positive predictive value, negative predictive value, and area under curve.",[58,59,60],"Deep Learning","Corneal Disease","Screening","2024-10-31",{"date":63,"type":64},"2024-11-04","ACTUAL",{"date":66,"type":64},"2020-12-06",{"date":68,"type":54},"2024-12-06",{"name":5,"class":6},1]