Detecting diabetic retinopathy through machine learning on electronic health record data from an urban, safety net healthcare system

OBJECTIVE: Clinical guidelines recommend annual eye examinations to detect diabetic retinopathy (DR) in patients with diabetes. However, timely DR detection remains a problem in medically underserved and under-resourced settings in the United States. Machine learning that identifies patients with la...

Descripción completa

Detalles Bibliográficos
Autores principales: Ogunyemi, Omolola I, Gandhi, Meghal, Lee, Martin, Teklehaimanot, Senait, Daskivich, Lauren Patty, Hindman, David, Lopez, Kevin, Taira, Ricky K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Research and Applications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374369/
https://www.ncbi.nlm.nih.gov/pubmed/34423259
http://dx.doi.org/10.1093/jamiaopen/ooab066

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374369/
https://www.ncbi.nlm.nih.gov/pubmed/34423259
http://dx.doi.org/10.1093/jamiaopen/ooab066

Ejemplares similares