Automated detection of type 1 ROP, type 2 ROP and A-ROP based on deep learning.

Eşay Kıran Yenice Caner KaraÇağatay Berke Erdaş

Published in: Eye (London, England) (2024)

Our study demonstrated that ROP classification by DL-based analysis of fundus images can be distinguished with high accuracy and specificity. Integrating DL-based artificial intelligence algorithms into clinical practice may reduce the workload of ophthalmologists in the future and provide support in decision-making in the management of ROP.

Keyphrases

deep learning
artificial intelligence
machine learning
convolutional neural network
big data
clinical practice
diabetic retinopathy
real time pcr