DEEP LEARNING-BASED PREDICTION OF OUTCOMES FOLLOWING NONCOMPLICATED EPIRETINAL MEMBRANE SURGERY.
Soo Han KimSoo Han KimSejung YangSung Soo KimJong Hyuck LeePublished in: Retina (Philadelphia, Pa.) (2022)
A deep learning model predicted the final CFT and CFT changes in patients 1 year after epiretinal membrane surgery. Central foveal thickness prediction showed the best results when demographic factors, comorbid diseases, and surgical techniques were considered.
Keyphrases
- deep learning
- minimally invasive
- coronary artery bypass
- end stage renal disease
- optical coherence tomography
- ejection fraction
- chronic kidney disease
- newly diagnosed
- surgical site infection
- machine learning
- prognostic factors
- peritoneal dialysis
- coronary artery disease
- patient reported outcomes
- percutaneous coronary intervention