This is the first study to do automated standardised labelling on FFA images. Our model is able to be applied in clinical practice, and will make great contributions to the development of intelligent diagnosis of FFA images.
Keyphrases
- deep learning
- diabetic retinopathy
- optical coherence tomography
- convolutional neural network
- artificial intelligence
- clinical evaluation
- end stage renal disease
- clinical practice
- machine learning
- newly diagnosed
- chronic kidney disease
- ejection fraction
- prognostic factors
- peritoneal dialysis
- computed tomography
- patient reported