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Real-time Artificial Intelligence System for Detecting Multiple Ocular Fundus Lesions by Ultra-widefield Fundus Imaging

NCT04859634 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 2000

Last updated 2021-04-26

No results posted yet for this study

Summary

This prospective multicenter study will evaluate the efficacy of a real-time artificial intelligence system for detecting multiple ocular fundus lesions by ultra-widefield fundus imaging in real-world settings.

Conditions

  • Artificial Intelligence
  • Diagnostic Imaging
  • Abnormality of the Fundus
  • Diagnostic Screening Programs

Interventions

DEVICE

Taking an ultra-widefield fundus image

The participant only needs to take an ultra-widefield fundus image as usual.

Sponsors & Collaborators

  • Shenzhen Eye Hospital

    collaborator OTHER

  • Xudong Ophthalmic Hospital

    collaborator UNKNOWN

  • IKang Physical Examination Center

    collaborator UNKNOWN

  • Beijing Tongren Hospital

    collaborator OTHER

  • Guangdong Provincial People's Hospital

    collaborator OTHER

  • Yangxi General Hospital People's Hospital

    collaborator UNKNOWN

  • Sun Yat-sen University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2020-11-01
Primary Completion
2022-02-01
Completion
2022-12-25

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 NCT04859634 on ClinicalTrials.gov