Performance of a Support Vector Machine Learning Tool for Diagnosing Diabetic Retinopathy in Clinical Practice

Performance of a Support Vector Machine Learning Tool for Diagnosing Diabetic Retinopathy in Clinical Practice

Purpose: To examine the real-world performance of a support vector machine learning software (RetinaLyze) in order to identify the possible presence of diabetic retinopathy (DR) in patients with diabetes via software implementation in clinical practice. Methods: 1001 eyes from 1001 patients—one eye...

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Bibliographic Details
Main Authors: Tobias P. H. Nissen, Thomas L. Nørgaard, Katja C. Schielke, Peter Vestergaard, Amar Nikontovic, Malgorzata Dawidowicz, Jakob Grauslund, Henrik Vorum, Kristian Aasbjerg
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Journal of Personalized Medicine
Subjects:
machine learning
diabetic retinopathy
screening
RetinaLyze
Online Access:https://www.mdpi.com/2075-4426/13/7/1128

Internet

https://www.mdpi.com/2075-4426/13/7/1128

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