An observational study in Ophthalmopathy and Artificial Intelligence, sponsored by Sun Yat-sen University. Completed at 1 site in China. Per ClinicalTrials.gov, last updated 2019-10-21.
Sponsored by Sun Yat-sen University · Observational
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.
388 studies on the registry are indexed under Eye Diseases; 62 are open to participants now.
This study's enrollment of 615 is above the median of 167 across 108 observational studies indexed under Eye Diseases.
Browse Eye Diseases studies →Sun Yat-sen University is the lead sponsor of 1,690 studies on the registry; 619 are open to participants now.
Counted across the registry records on this site, refreshed daily.
A prospective study of patients and residents who use the web platform for diagnosis.
Inclusion Criteria:
Device: ophthalmology diagnostic system. An artificial intelligence to make comprehensive evaluation and treatment decision of ocular diseases.
Device: Ophthalmology diagnostic system.
An artificial intelligence to make comprehensive evaluation and treatment decision of ocular diseases.
The proportion of accurate, mistaken and miss detection of the ophthalmology diagnostic system.
Time frame: Up to 5 years
This study is completed, as verified in Oct 2019. You cannot join it, but the record below documents what was studied.
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