EyeNet
ICML 18 workshop - A Novel Hybrid Machine Learning Model for Auto-Classification of Retinal Diseases
Install / Use
/learn @huckiyang/EyeNetREADME
EyeNet
A Machine Learning algorithm framework (SVM+DNNs) has been accepted at ICML-IJCAI Workshop of CompBio 2018

EyeNet contains machine learning models and disease's labels for medical informatics and machine learning research
Reference
https://arxiv.org/abs/1806.06423
If you find this useful in your work, please consider citing the following reference:
@article{yang2018novel,
title={A Novel Hybrid Machine Learning Model for Auto-Classification of Retinal Diseases},
author={Yang, C-H Huck and Huang, Jia-Hong and Liu, Fangyu and Chiu, Fang-Yi and Gao, Mengya and Lyu, Weifeng and Tegner, Jesper and others},
journal={arXiv preprint arXiv:1806.06423},
year={2018}
}
Only viewing the original images by the index number from the Retina Image Bank (RIB) for an educational or academic purpose
Please only access the Images via Retina Image Bank Website. A full credit index has been set in each folder of a specific disease.
http://imagebank.asrs.org/
Please follow RIB's using credit and privacy during the data processing
http://imagebank.asrs.org/terms-of-use#contributors
http://imagebank.asrs.org/terms-of-use#visitors
“This image was originally published in the Retina Image Bank. Author. Photographer. Title. Retina Image Bank. Year; Image Number. © the American Society of Retina Specialists."
All other rights reserved.
Contact imagebank@asrs.org with copyright or use questions.
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