Identifying the severity of diabetic retinopathy by visual function measures using both traditional statistical methods and interpretable machine learning: a cross-sectional study

AIMS/HYPOTHESIS: To determine the extent to which diabetic retinopathy severity stage may be classified using machine learning (ML) and commonly used clinical measures of visual function together with age and sex. METHODS: We measured the visual function of 1901 eyes from 1032 participants in the No...

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Detalles Bibliográficos
Autores principales: Wright, David M., Chakravarthy, Usha, Das, Radha, Graham, Katie W., Naskas, Timos T., Perais, Jennifer, Kee, Frank, Peto, Tunde, Hogg, Ruth E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10627908/
https://www.ncbi.nlm.nih.gov/pubmed/37725107
http://dx.doi.org/10.1007/s00125-023-06005-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10627908/
https://www.ncbi.nlm.nih.gov/pubmed/37725107
http://dx.doi.org/10.1007/s00125-023-06005-3

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