Receiver operating characteristic (ROC) curves were used for differentiating different retinal vascular diseases and treatment-requiring diseases, and the area under the curve (AUC) was measured for each ROC curve. Moreover, the sensitivity, specificity, and accuracy of the model were calculated. Regarding model performance in predicting different retinal diseases, the AUC, sensitivity, specificity, and accuracy were based on a one-versus-rest comparison. Additionally, a confusion matrix was created and demonstrated sensitivity in disease prediction. Statistical analysis was performed using the Sklearn 0.23.2 package in Python (Python Software Foundation).

Note: The content above has been extracted from a research article, so it may not display correctly.



Q&A
Please log in to submit your questions online.
Your question will be posted on the Bio-101 website. We will send your questions to the authors of this protocol and Bio-protocol community members who are experienced with this method. you will be informed using the email address associated with your Bio-protocol account.



We use cookies on this site to enhance your user experience. By using our website, you are agreeing to allow the storage of cookies on your computer.