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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Detalles Bibliográficos
Autores principales: Nissen, Tobias P. H., Nørgaard, Thomas L., Schielke, Katja C., Vestergaard, Peter, Nikontovic, Amar, Dawidowicz, Malgorzata, Grauslund, Jakob, Vorum, Henrik, Aasbjerg, Kristian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10381514/
https://www.ncbi.nlm.nih.gov/pubmed/37511741
http://dx.doi.org/10.3390/jpm13071128

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10381514/
https://www.ncbi.nlm.nih.gov/pubmed/37511741
http://dx.doi.org/10.3390/jpm13071128

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