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Clinical Trials/NCT03499145
NCT03499145
Completed
Not Applicable

Validation of the Utility of Ophthalmology Intelligent Diagnostic System: A Clinical Trial

Sun Yat-sen University1 site in 1 country615 target enrollmentApril 1, 2018

Overview

Phase
Not Applicable
Intervention
Not specified
Conditions
Ophthalmopathy
Sponsor
Sun Yat-sen University
Enrollment
615
Locations
1
Primary Endpoint
The proportion of accurate, mistaken and miss detection of the ophthalmology diagnostic system.
Status
Completed
Last Updated
6 years ago

Overview

Brief Summary

The prevention and treatment of diseases via artificial intelligence represents an ultimate goal in computational medicine. Application scenarios of the current medical algorithms are too simple to be generally applied to real-world complex clinical settings. Here, the investigators use "deep learning" and "visionome technique", an novel annotation method for artificial intelligence in medical, to create an automatic detection and classification system for four key clinical scenarios: 1) mass screening, 2) comprehensive clinical triage, 3) hyperfine diagnostic assessment, and 4) multi-path treatment planning. The investigator also establish a telemedicine system and conduct clinical trial and website-based study to validate its versatility.

Registry
clinicaltrials.gov
Start Date
April 1, 2018
End Date
August 31, 2019
Last Updated
6 years ago
Study Type
Observational
Sex
All

Investigators

Sponsor
Sun Yat-sen University
Responsible Party
Principal Investigator
Principal Investigator

Haotian Lin

Clinical Professor

Sun Yat-sen University

Eligibility Criteria

Inclusion Criteria

  • Patients and residents who underwent ophthalmic examination of the eye and recorded their ocular information in the outpatient clinic and community.

Exclusion Criteria

  • Not provided

Outcomes

Primary Outcomes

The proportion of accurate, mistaken and miss detection of the ophthalmology diagnostic system.

Time Frame: Up to 5 years

Study Sites (1)

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