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Validation of the Utility of Ophthalmology Intelligent Diagnostic System

Sun Yat-sen University logo

Sun Yat-sen University

Status

Completed

Conditions

Ophthalmopathy
Artificial Intelligence

Treatments

Device: Ophthalmology diagnostic system.

Study type

Observational

Funder types

Other

Identifiers

NCT03499145
CCPMOH2018-China-2

Details and patient eligibility

About

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.

Enrollment

615 patients

Sex

All

Volunteers

Accepts Healthy Volunteers

Inclusion and exclusion criteria

Inclusion Criteria:

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

Trial design

615 participants in 1 patient group

Eligible patients for AI test.
Description:
Device: ophthalmology diagnostic system. An artificial intelligence to make comprehensive evaluation and treatment decision of ocular diseases.
Treatment:
Device: Ophthalmology diagnostic system.

Trial contacts and locations

1

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Data sourced from clinicaltrials.gov

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