Machine Learning in the Detection of the Glaucomatous Disc and Visual Field.
David J SmitsTobias ElzeHaobing WangLouis R PasqualePublished in: Seminars in ophthalmology (2019)
Glaucoma is the leading cause of irreversible blindness worldwide. Early detection is of utmost importance as there is abundant evidence that early treatment prevents disease progression, preserves vision, and improves patients' long-term quality of life. The structure and function thresholds that alert to the diagnosis of glaucoma can be obtained entirely via digital means, and as such, screening is well suited to benefit from artificial intelligence and specifically machine learning. This paper reviews the concepts and current literature on the use of machine learning for detection of the glaucomatous disc and visual field.
Keyphrases
- machine learning
- artificial intelligence
- big data
- optic nerve
- end stage renal disease
- deep learning
- ejection fraction
- chronic kidney disease
- newly diagnosed
- loop mediated isothermal amplification
- systematic review
- peritoneal dialysis
- prognostic factors
- randomized controlled trial
- optical coherence tomography
- cataract surgery
- clinical decision support
- smoking cessation