Deep Learning vs. Human Graders for Classifying Severity Levels of Diabetic Retinopathy in a Real-World Nationwide Screening Program.
Paisan RaumviboonsukJonathan KrausePeranut ChotcomwongseRory SayresRajiv RamanKasumi WidnerBilson J. L. CampanaSonia PheneKornwipa HemaratMongkol TadaratiSukhum Silpa-ArchaJirawut LimwattanayingyongChetan RaoOscar KuruvillaJesse JungJeffrey TanSurapong OrprayoonChawawat KangwanwongpaisanRamase SukulmalpaiboonChainarong LuengchaichawangJitumporn FuangkaewPipat KongsapLamyong ChualinphaSarawuth SareeSrirat KawinpanitanKorntip MitvongsaSiriporn LawanasakolChaiyasit ThepchatriLalita WongpichedchaiGregory S. CorradoLily PengDale R. WebsterPublished in: CoRR (2018)
Keyphrases
- diabetic retinopathy
- deep learning
- real world
- automatic detection
- retinal images
- early detection
- optic disc
- unsupervised learning
- unsupervised feature learning
- medical experts
- machine learning
- data sets
- blood vessels
- data mining
- object recognition
- lung cancer
- weakly supervised
- computer vision
- mental models
- higher order
- co occurrence
- knowledge discovery
- expert systems
- vessel segmentation
- feature space