Predicting diabetic retinopathy and identifying interpretable biomedical features using machine learning algorithms

Predicting diabetic retinopathy and identifying interpretable biomedical features using machine learning algorithms

Abstract Background The risk factors of diabetic retinopathy (DR) were investigated extensively in the past studies, but it remains unknown which risk factors were more associated with the DR than others. If we can detect the DR related risk factors more accurately, we can then exercise early preven...

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Bibliographic Details
Main Authors: Hsin-Yi Tsao, Pei-Ying Chan, Emily Chia-Yu Su
Format: Article
Language:English
Published: BMC 2018-08-01
Series:BMC Bioinformatics
Subjects:
Diabetic retinopathy
Clinical decision support
Machine learning
Risk factors
Online Access:http://link.springer.com/article/10.1186/s12859-018-2277-0

Internet

http://link.springer.com/article/10.1186/s12859-018-2277-0

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