An observational study in Artificial Intelligence, Ophthalmology and Kidney Diseases, sponsored by Sun Yat-sen University. Status unknown at 1 site in China. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2022-02-04.
Sponsored by Sun Yat-sen University · Observational
This is an retrospective and prospective multicenter study to develop and validate an artificial intelligent (AI) aided diagnosis, therapeutic effect assessment model including chronic kidney disease (CKD) and dialysis patients starting from April 2009, which is based on ophthalmic examinations (e.g. retinal fundus photography, slit-lamp images, OCTA, etc.) and CKD diagnostic and therapeutic data (routine clinical evaluations and laboratory data), to provide a reliable basis and guideline for clinical diagnosis and treatment.
3,840 studies on the registry are indexed under Kidney Diseases; 500 are open to participants now.
This study's planned enrollment of 4,000 is above the median of 192 across 1,033 observational studies indexed under Kidney Diseases.
Browse Kidney Diseases studies →Sun Yat-sen University is the lead sponsor of 1,644 studies on the registry; 602 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Participants who had slit-lamp, retinal fundus photography and kidney disease tests at the Department of Nephrology, First Affiliated Hospital of Sun Yat-sen University and Medical Centre of Aikang Health Care, Guangzhou, China
Exclusion Criteria:
Slit-lamp, retinal fundus images, OCTA and kidney diseases examinations collected from Department of Nephrology of the First Affiliated Hospital of Sun Yat-sen University
Other: Diagnostic Test: Chronic Kidney Diseases
Slit-lamp, retinal fundus images, OCTA and kidney diseases examinations collected from Medical Centre of Aikang Health Care, Guangzhou, China
Other: Diagnostic Test: Chronic Kidney Diseases
Slit-lamp, retinal fundus images, OCTA and kidney diseases examinations collected from Department of Nephrology of the First Affiliated Hospital of Sun Yat-sen University
Other: Diagnostic Test: Chronic Kidney Diseases
Slit-lamp, retinal fundus images, OCTA and kidney diseases examinations collected from Medical Centre of Aikang Health Care, Guangzhou, China
Other: Diagnostic Test: Chronic Kidney Diseases
Slit-lamp, retinal fundus images, OCTA and kidney diseases examinations collected from Department of Nephrology of the First Affiliated Hospital of Sun Yat-sen University
Other: Diagnostic Test: Chronic Kidney Diseases
Slit-lamp, retinal fundus images, OCTA and kidney diseases examinations collected from Medical Centre of Aikang Health Care, Guangzhou, China
Other: Diagnostic Test: Chronic Kidney Diseases
The development datasets were used to train the deep learning model, which was validated and tested by the other 4 datasets.
Area under the receiver operating characteristic curve of the deep learning system
The investigators will calculate the area under the receiver operating characteristic curve of deep learning system and compare this index between deep learning system and human doctors
Time frame: baseline
Sensitivity and specificity of the deep learning system
The investigators will calculate the sensitivity and specifity of deep learning system and compare this index between deep learning system and human doctors
Time frame: baseline
Plan to share: No
No publications or documents are linked to this record.
This study is status unknown, as verified in Jan 2022. You cannot join it, but the record below documents what was studied.
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Sun Yat-sen University