Ros-NET: A deep convolutional neural network for automatic identification of rosacea lesions.

Hamidullah BinolAlisha PlotnerJennifer SopkovichBenjamin Harris Kaffenberger Muhammad Khalid Khan Niazi Metin Nafi Gurcan

Published in: Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) (2019)

The findings from this study support that pre-trained networks trained via transfer learning can be beneficial in identifying rosacea lesions. Our future work will involve expanding the work to a larger database of cases with varying degrees of disease characteristics.

Keyphrases

convolutional neural network
deep learning
resistance training
dna damage
cell death
machine learning
reactive oxygen species
neural network
drug induced
electron transfer
network analysis