[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100627387":3},{"organization":4,"armGroups":7,"interventions":18,"overallOfficials":10,"centralContacts":24,"locations":30,"responsibleParty":47,"collaborators":10,"id":49,"slug":50,"hasResults":51,"nctId":52,"briefTitle":53,"officialTitle":54,"acronym":10,"eligibilityCriteria":55,"healthyVolunteers":56,"sex":57,"minAge":58,"maxAge":10,"enrollmentInfo":59,"targetDuration":10,"studyType":62,"phases":10,"briefSummary":63,"conditions":64,"keywords":66,"overallStatus":33,"whyStopped":10,"lastUpdateSubmitDate":68,"lastUpdatePostDateStruct":69,"startDateStruct":72,"completionDateStruct":74,"leadSponsor":76,"locationsCount":77},{"fullName":5,"class":6},"Guangdong Provincial People's Hospital","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Normal participants",null,"Healthy individuals who have no concerns related to their eyes.",[13],"Diagnostic Test: Multimodal Vision-language Model Diagnosis",{"label":15,"type":10,"description":16,"interventionNames":17},"Patients with Eye-related Chief Complaints","Individuals who have specific concerns or issues related to their eyes, which they consider as the main reason for seeking medical attention or making a complaint.",[13],[19],{"type":20,"name":21,"description":22,"armGroupLabels":23,"otherNames":10},"DIAGNOSTIC_TEST","Multimodal Vision-language Model Diagnosis","Multimodal Vision-language Model for Multi-task Diagnosis and Triage Suggestions of Ophthalmic Diseases Patients presenting with complaints of anterior segment diseases first complete a slit-lamp examination or take a mobile phone eye photograph. A multimodal vision-language model uses patient-related images (such as selfies and eye exam photos) to make an intelligent diagnosis. The diagnosis is kept private. The patient then seeks medical attention and undergoes a clinical examination by an experienced clinician. A second experienced clinician then reviews the clinical diagnosis. If the diagnosis agrees, it is considered the gold standard. If there is a discrepancy in the diagnosis, the consensus between the two clinicians is used as the gold standard.",[9,15],[25],{"name":26,"role":27,"phone":28,"phoneExt":10,"email":29},"Honghua Yu","CONTACT","+8618688888422","yuhonghua@gdph.org.cn",[31],{"facility":32,"status":33,"city":34,"state":35,"zip":36,"country":37,"countryCode":38,"cosmosGeoPoint":39,"geoPoint":44,"contacts":45},"Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University","RECRUITING","Guangzhou","Guangdong","510280","China","CN",{"type":40,"coordinates":41},"Point",[42,43],113.25,23.11667,{"lat":43,"lon":42},[46],{"name":26,"role":27,"phone":28,"phoneExt":10,"email":29},{"type":48,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR","100627387","multimodal-deep-learning-model-for-multi-task-diagnosis-and-triage-suggestions-of-ophthalmic-diseases-100627387",false,"NCT07447973","Multimodal Deep Learning Model for Multi-task Diagnosis and Triage Suggestions of Ophthalmic Diseases","Development and Validation of Multimodal Deep Learning Model for Autonomous Diagnosis, Generative Reporting, and Specialist Referral in Ophthalmic Diseases: An International Multicenter Cohort Study","Inclusion Criteria:\n\n1. Informed consent obtained;\n2. Participants should be sufficiently able to read, write, and understand Chinese or English;\n3. For normal participants: individuals should have no concerns related to their eyes.\n4. For participants with eye-related chief complaints: individuals should have specific concerns or issues related to their eyes.\n\nExclusion Criteria:\n\n1. Incomplete clinical data to support final diagnosis;\n2. Patients who, in the opinion of the attending physician or clinical study staff, are too medically unstable to participate in the study safely.",true,"ALL","18 Years",{"count":60,"type":61},2000,"ESTIMATED","OBSERVATIONAL","Accurate and comprehensive interpretation of anterior segment diseases from slit-lamp and smartphone photographs remains a clinical challenge due to the limited specificity and structure of existing Artificial Intelligence tools. The purpose of this international, multicenter clinical trial is to developed and validated an agent-based framework that integrates vision-language models and large language models to enhance the diagnostic workflow of anterior segment diseases.",[65],"Anterior Segment Diseases",[65,67],"Artificial Intelligence","2026-03-03",{"date":70,"type":71},"2026-03-05","ACTUAL",{"date":73,"type":71},"2025-07-28",{"date":75,"type":61},"2027-12-31",{"name":5,"class":6},1]