A deep learning approach to investigate the filtration bleb functionality after glaucoma surgery: a preliminary study.
Leonardo MastropasquaLuca AgnifiliLorenza BresciaMichele FigusChiara PosarelliFrancesco OddoneSara GiammariaMatteo SacchiMarco PavanDante Degli InnocentiValentina OlivottoStefano L SensiRodolfo MastropasquaPublished in: Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie (2023)
All considered metrics supported that the final DL model was able to discriminate functioning from failed FBs, with good accuracy. This approach could support clinicians in the patients' management after glaucoma surgery in absence of adjunctive clinical data.
Keyphrases
- minimally invasive
- coronary artery bypass
- deep learning
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- surgical site infection
- machine learning
- electronic health record
- optic nerve
- prognostic factors
- artificial intelligence
- acute coronary syndrome
- percutaneous coronary intervention
- optical coherence tomography
- atrial fibrillation
- cataract surgery