The investigators aim to improve the diagnostic accuracy and the clinical referral rate for diabetic retinopathy by using a deep learning-based software.
Diabetic retinopathy (DR) is the leading cause of blindness among working-age patients with type 2 diabetes. According to previous studies, early screening and timely treatment can reduce the risk of worsening DR and blindness. International guidelines recommend that screening for DR be performed at least once every year for patients with type 2 diabetes. The investigators will implement a validated deep learning-based software, VeriSee®, in clinics, and evaluate the benefits on diagnostic accuracy and the clinical referral rate for diabetic retinopathy after implementation of this software.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
SCREENING
Masking
NONE
Enrollment
1,000
Screening of diabetic retinopathy using a validated deep learning-based software,VeriSee®
Division of Endocrinology and Metabolism in Taichung Veterans General Hospital
Taichung, Taiwan
diagnostic accuracy
diagnostic accuracy compared to the baseline
Time frame: 12 months
Screening rate of diabetic retinopathy
Screening rate of diabetic retinopathy in patients with diabetes
Time frame: 12 months
Changes in HbA1c
Changes in HbA1c
Time frame: 3 months
Referral rate of diabetic retinopathy
Successful referral rate for referrable diabetic retinopathy
Time frame: 12 months
Yu-Hsuan Li, MD
CONTACT
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