This paper reports on the application of an artificial neural network to the clinical analysis of
ophthalmological data. In particular a 2-dimensional Kohonen self-organising feature map
(SOM) is used to analyse visual field data from glaucoma patients. Importantly, the paper
addresses the problem of how the SOM can be utilised to accommodate the noise within the
data. This is a particularly important problem within longitudinal assessment, where
detecting significant change is the crux of the problem in clinical diagnosis. Data from 737 …