Optical Coherence Tomography Machine Learning Classifiers for Glaucoma Detection: A Preliminary Study - Burgansky-Eliash, Zvia; Wollstein, Gadi; Chu, Tianjiao; Ramsey, Joseph D; Glymour, Clark; Noecker, Robert J; Ishikawa, Hiroshi; Schuman, Joel S (Investigative ophthalmology & visual science, 2005)
Keywords: Adult; Aged; Aged, 80 and over; Biological and medical sciences; Cross-Sectional Studies; Diagnostic Techniques, Ophthalmological - classification; Eye and associated structures. Visual pathways and centers. Vision; Female; Fundamental and applied biological sciences. Psychology; Glaucoma and intraocular pressure; Glaucoma, Open-Angle - classification; Glaucoma, Open-Angle - diagnosis; Humans; Intraocular Pressure; Male; Medical sciences; Middle Aged; Nerve Fibers - parasitology; Neural Networks, Computer; Ophthalmology; Optic Nerve Diseases - diagnosis; Pilot Projects; Reproducibility of Results; Retinal Ganglion Cells - parasitology; ROC Curve; Sensitivity and Specificity; Tomography, Optical Coherence - classification; Vertebrates: nervous system and sense organs; Learning; Glaucoma; Protozoa; Eye disease; Optical coherence tomography; Glaucoma (eye); Ciliata; Ophthalmology; Medical screening; Detection