{"type":"trials","record":{"id":41673,"source_id":"clinicaltrials-gov","external_id":"NCT07249307","title":"High-throughput Large-model-based AI-assisted Diagnosis Using OCT","brief_summary":"This observational study aims to establish key technologies for high-throughput, large-model-based AI-assisted diagnosis using optical coherence tomography (OCT) and OCT angiography (OCTA). The study will collect real-world OCT/OCTA images and corresponding clinical information from patients with common blinding retinal and optic nerve diseases at Peking Union Medical College Hospital. A high-throughput diagnostic framework based on large-scale artificial intelligence models will be developed and evaluated. The primary objective is to determine the diagnostic performance of the AI system, including its ability to identify diabetic retinopathy, branch retinal vein occlusion, central retinal vein occlusion, age-related macular degeneration, pathologic myopic choroidal neovascularization, and glaucoma-related optic nerve damage. The results of this study are expected to support the development of standardized, efficient, and scalable AI-assisted diagnostic pathways for OCT imaging in clinical practice.","overall_status":"Not Yet Recruiting","phases":[],"study_type":"OBSERVATIONAL","sponsor":"Peking Union Medical College Hospital","enrollment":2000,"countries":[],"start_date":"2025-11-30","completion_date":"2028-12-31","last_update_date":"2025-11-25","source_url":"https://clinicaltrials.gov/study/NCT07249307","editorial_summary":"A registered study indexed because it matched monitored longevity research terms. Registry status: Not Yet Recruiting. Registration does not establish safety or effectiveness.","first_seen_at":"2026-09-25T01:25:30.378222+00:00","last_seen_at":"2026-09-25T06:20:47.789+00:00","metadata":{"sex":"ALL","acronym":null,"age_range":null,"comparator":null,"organization":"Peking Union Medical College Hospital","interventions":["No intervention"],"registry_source":"ClinicalTrials.gov","outcome_measures":["Diagnostic performance of the AI-assisted OCT/OCTA model (AUC for multi-disease classification) — Baseline imaging visi…","Sensitivity and specificity of the AI-assisted OCT/OCTA model — At the time of image acquisition and model inference (b…","Agreement between AI-assisted diagnosis and clinician diagnosis — At the time of image acquisition and model inference…"],"design_description":null,"source_has_results":false},"controlled_terms":["Diabetic Retinopathy (DR)","Retinal Vein Occlusion (RVO)","Age-Related Macular Degeneration (AMD)","Pathologic Myopia","Glaucoma","No intervention"],"relevance_confidence":100,"source_quality_score":100,"freshness_score":85,"publication_state":"published","match_explanation":"Abstract contains controlled term: age-related macular degeneration.","quality_checked_at":"2026-09-25T06:20:59.355028+00:00","duplicate_cluster_key":"id:nct07249307","duplicate_of_id":null,"evidence_snapshot":{"status":"structured","version":1,"duration":"2025-11-30 to 2028-12-31","comparator":null,"confidence":"structured-source","population":"ALL","provenance":{"duration":"start_date and completion_date","comparator":"registry arm fields","population":"registry eligibility fields","intervention":"registry intervention fields","participants":"enrollment","study_design":"study_type and registry design fields","evidence_stage":"phases","reported_outcome":"not available","outcomes_measured":"registry outcome-measure fields"},"generated_at":"2026-09-25T06:20:47.851Z","intervention":["No intervention"],"participants":2000,"study_design":"OBSERVATIONAL","subject_scope":"Human clinical study registration","evidence_stage":"Phase not reported","safety_context":"Eligibility, adverse-event details, and clinical decisions must be checked in the official registry and with qualified clinicians.","source_support":"Structured registry protocol metadata; no finding-level conclusion is generated.","main_limitation":"This is a study registration. No reusable structured result is available here, so it cannot show whether the intervention worked or was safe.","reported_outcome":null,"outcomes_measured":["Diagnostic performance of the AI-assisted OCT/OCTA model (AUC for multi-disease classification) — Baseline imaging visi…","Sensitivity and specificity of the AI-assisted OCT/OCTA model — At the time of image acquisition and model inference (b…","Agreement between AI-assisted diagnosis and clinician diagnosis — At the time of image acquisition and model inference…"],"regulatory_context":"Trial registration is not regulatory approval and does not establish that an intervention is available."},"clinical_trial_topics":[{"topic_slug":"vision-aging","is_published":true,"match_reasons":["Abstract contains controlled term: age-related macular degeneration.","Source terminology contains: age-related macular degeneration.","Abstract supplies longevity context: aging, age-related.","Study type is explicitly identified as OBSERVATIONAL."],"matched_fields":["abstract","controlled terminology","abstract context","study type"],"relevance_score":100,"intelligence_topics":{"name":"Vision ageing","slug":"vision-aging"}}],"content_sources":{"name":"ClinicalTrials.gov","homepage_url":"https://clinicaltrials.gov/"}},"canonical_url":"https://www.immortal.life/trials/41673","automation_disclosure":"Generated automatically from cited source metadata. No scientist, clinician, researcher, editor, or human reviewer evaluates this publication before release."}