Paring Neural Networks and Linear Discriminant Functions for Glaucoma
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چکیده
assessment of atypical birefringence images using scanning laser polarime-try with variable corneal compensation. New algorithms for multi-class cancer diagnosis using tumor gene expression signatures. The protein data bank: a computer-based archival file for macromolecular structures. Substructure-based support vector machine classifiers for prediction of adverse effects in diverse classes of drugs.
منابع مشابه
Comparing neural networks and linear discriminant functions for glaucoma detection using confocal scanning laser ophthalmoscopy of the optic disc.
PURPOSE To determine whether neural network techniques can improve differentiation between glaucomatous and nonglaucomatous eyes, using the optic disc topography parameters of the Heidelberg Retina Tomograph (HRT; Heidelberg Engineering, Heidelberg, Germany). METHODS With the HRT, one eye was imaged from each of 108 patients with glaucoma (defined as having repeatable visual field defects wit...
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تاریخ انتشار 2005