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.
Study Type
OBSERVATIONAL
Enrollment
4,000
The development datasets were used to train the deep learning model, which was validated and tested by the other 4 datasets.
Zhongshan Ophthalmic Center, Sun Yat-sen University
Guangzhou, Guangdong, China
RECRUITINGArea 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
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