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Explainable Ocular Fundus Diseases Report Generation System

NCT05622565 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 15000

Last updated 2023-07-11

No results posted yet for this study

Summary

To establish a deep learning system of various ocular fundus disease analytics based on the results of multimodal examination images. The system can analyze multimodal ocular fundus images, make diagnoses and generate corresponding reports.

Conditions

  • Ophthalmological Disorder
  • Image, Body

Interventions

DIAGNOSTIC_TEST

Various modalities of ocular fundus imaging

Through various modalities of ocular fundus imaging, combining with clinical data and the experience of clinicians to diagnose different fundus diseases.

Sponsors & Collaborators

  • Sun Yat-sen University

    lead OTHER

Principal Investigators

  • Yingfeng Zheng, M.D. Ph.D · Zhongshan Ophthalmic Center, Sun Yat-sen Univerisity,Guangzhou, Guangdong, China, 510060

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2011-01-31
Primary Completion
2023-12-31
Completion
2024-07-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05622565 on ClinicalTrials.gov