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The automated recognition of the visual field defect type from results of visual field testing is crucial for the adequate diagnosis and treatment of the underlying disease of the visual system. This paper presents a reliable rule-based classifier that emulates the decision strategies of expert ophthalmologists based on a two-level approach that combines methods of unsupervised learning.
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Kasneci et al. (2014) studied this question.