Therapeutic response in the HAWK and HARRIER trials using deep learning in retinal fluid volume and compartment analysis.
Ursula Margarethe Schmidt-ErfurthZufar MulyukovBianca S GerendasGregor Sebastian ReiterDaniel LorandGeorges WeissgerberHrvoje BogunovicPublished in: Eye (London, England) (2022)
Deep-learning methods allow an accurate assessment of substance and regimen efficacy. Irrespectively, all fluid compartments were found to be important markers of disease activity and were relevant for visual outcomes.
Keyphrases
- deep learning
- disease activity
- systemic lupus erythematosus
- rheumatoid arthritis
- rheumatoid arthritis patients
- ankylosing spondylitis
- artificial intelligence
- convolutional neural network
- juvenile idiopathic arthritis
- machine learning
- optical coherence tomography
- diabetic retinopathy
- high resolution
- type diabetes
- insulin resistance
- optic nerve
- weight loss