[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100631218":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":20,"centralContacts":24,"locations":32,"responsibleParty":64,"collaborators":67,"id":69,"slug":70,"hasResults":71,"nctId":72,"briefTitle":73,"officialTitle":74,"acronym":75,"eligibilityCriteria":76,"healthyVolunteers":77,"sex":78,"minAge":79,"maxAge":10,"enrollmentInfo":80,"targetDuration":10,"studyType":83,"phases":10,"briefSummary":84,"conditions":85,"keywords":91,"overallStatus":96,"whyStopped":10,"lastUpdateSubmitDate":97,"lastUpdatePostDateStruct":98,"startDateStruct":101,"completionDateStruct":103,"leadSponsor":105,"locationsCount":106},{"fullName":5,"class":6},"Iriscience Inc","INDUSTRY",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"Images of patients over 18 years old",null,"This is a diagnostic validation study without intervention. All images are analyzed using the same methodology. There are no comparison groups, treatment arms, or cohorts. The study evaluates AI system performance against expert ophthalmologist diagnoses (ground truth).",[13],"Other: No interventions",[15],{"type":16,"name":17,"description":18,"armGroupLabels":19,"otherNames":10},"OTHER","No interventions","This retrospective observational study involves no therapeutic interventions, no treatment modifications, no patient contact, and no comparison groups. It is purely diagnostic technology development and validation using existing historical data.",[9],[21],{"name":22,"affiliation":5,"role":23},"Marisse Masis-Solano","STUDY_DIRECTOR",[25,30],{"name":26,"role":27,"phone":28,"phoneExt":10,"email":29},"Marissé Masís Solano, MD PhD","CONTACT","19293278463","marisse@irisciencetech.com",{"name":31,"role":27,"phone":10,"phoneExt":10,"email":29},"Lihteh Wu, MD",[33,50],{"facility":34,"status":10,"city":35,"state":36,"zip":10,"country":37,"countryCode":38,"cosmosGeoPoint":39,"geoPoint":44,"contacts":45},"Centro Ocular","Heredia","Centro","Costa Rica","CR",{"type":40,"coordinates":41},"Point",[42,43],-84.11587,9.99872,{"lat":43,"lon":42},[46],{"name":47,"role":27,"phone":48,"phoneExt":10,"email":49},"Erick Hernandez, MD","+50660075434","erickherbog@gmail.com",{"facility":51,"status":10,"city":52,"state":53,"zip":10,"country":37,"countryCode":38,"cosmosGeoPoint":54,"geoPoint":58,"contacts":59},"Asociados de Mácula y Vítreo de Costa Rica","San José","Provincia de San José",{"type":40,"coordinates":55},[56,57],-84.08489,9.93388,{"lat":57,"lon":56},[60],{"name":61,"role":27,"phone":10,"phoneExt":62,"email":63},"Lihteh Lihteh Wu, MD","+506 83221200","lihteh@gmail.com",{"type":65,"investigatorFullName":22,"investigatorTitle":66,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"SPONSOR_INVESTIGATOR","Collaborator",[68],{"name":5,"class":6},"100631218","artificial-intelligence-assisted-diagnosis-in-ophthalmology-100631218",false,"NCT07497815","Artificial Intelligence-assisted Diagnosis in Ophthalmology","Development and Validation of an Artificial Intelligence-assisted Diagnostic System for Ophthalmic Pathologies","AI-OPHTH-CR","Inclusion Criteria:\n\n* Image corresponds to patient ≥18 years of age at time of capture\n* Image modality is one of: fundus photography, posterior segment OCT, anterior segment photography, automated perimetry, or video-OCT\n* Image quality sufficient for diagnostic interpretation (adequate resolution, focus, illumination, complete visualization of anatomical area of interest, no major artifacts)\n* Minimum clinical data available (age or age group, sex, and diagnosis or clinical indication)\n* Image captured during routine clinical care (not specifically for research)\n* No patient objection to use of medical data for research (when applicable per center policy)\n\nExclusion Criteria:\n\nCLINICAL:\n\n* Images from eyes with recent intraocular surgery (\\\u003C3 months)\n* Images from eyes with severe ocular trauma distorting anatomy\n* Images from patients with rare or unique ocular pathologies not allowing generalization\n* Images post-recent laser treatment where acute changes may confuse analysis\n\nTECHNICAL:\n\n* Severely degraded image quality (extreme blur, severe under\u002Foverexposure, major artifacts preventing interpretation)\n* Duplicate images of same eye on same date\n* Images with missing or clearly erroneous metadata\n* Images in non-standard or corrupted formats that cannot be processed\n\nSex\u002FGender: All Minimum Age: 18 Years Maximum Age: No limit Accepts Healthy Volunteers: Yes (images of healthy eyes without pathology are included as controls)",true,"ALL","18 Years",{"count":81,"type":82},15000,"ESTIMATED","OBSERVATIONAL","This is a retrospective, multicenter, observational study designed to develop and validate an artificial intelligence (AI) system capable of detecting and classifying major ophthalmic diseases (glaucoma, cataract, diabetic retinopathy, and other retinal pathologies) in the Costa Rican population. The study will use approximately 15,000 existing medical images from digital archives of two ophthalmic centers in Costa Rica, without active participant recruitment or capture of new images.\n\nThe primary motivation is that AI systems developed in other countries (primarily Asian, European, or North American populations) do not necessarily perform with the same accuracy when applied to Latin American populations. This study seeks to establish a precedent for the importance of locally validating any medical AI technology before clinical implementation.",[86,87,88,89,90],"Macular Degeneration","Diabetic Retinopathy (DR)","Glaucoma","Keratoconus","Cataract",[92,93,94,95],"artificial inteligence","ophthalmology","imaging","bias","NOT_YET_RECRUITING","2026-03-26",{"date":99,"type":100},"2026-04-01","ACTUAL",{"date":102,"type":82},"2026-05-01",{"date":104,"type":82},"2029-05-01",{"name":22,"class":6},2]