Open AccessUsing Metabolic and Biochemical Indicators to Predict Diabetic Retinopathy by Back-Propagation Artificial Neural Network
Author(s) -
Bo Su
Publication year - 2021
Publication title -
diabetes, metabolic syndrome and obesity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.853
H-Index - 43
ISSN - 1178-7007
DOI - 10.2147/dmso.s322224
Subject(s) - logistic regression , diabetic retinopathy , medicine , diabetes mellitus , receiver operating characteristic , artificial neural network , backpropagation , linear regression , type 2 diabetes mellitus , creatinine , retinopathy , sigmoid function , regression analysis , mathematics , statistics , artificial intelligence , endocrinology , computer science
Timely diagnosis of diabetic retinopathy (DR) can significantly improve the prognosis of patients. In this study, we established a prediction model by analyzing the relationship between diabetic retinopathy and related metabolic and biochemical indicators.