Machine Learning Applied to Optometry Data Beatriz Remeseiro López en Barreira,N en Sánchez Brea,L en Ramos,L en Mosquera,A en 2018-01-17T11:01:58Z 2018-01-17T11:01:58Z 2018 en
dc.description.abstract Optometry is the primary health care of the eye and visual system. It involves detecting defects in vision, signs of injury, ocular diseases as well as problems with general health that produce side effects in the eyes. Myopia, presbyopia, glaucoma or diabetic retinopathy are some examples of conditions that optometrists usually diagnose and treat. Moreover, there is another condition that we have all experienced once in a while, especially if we work with computers or have been exposed to smoke or wind. Dry eye syndrome (DES) is a hidden multifactorial disease related with the quality and quantity of tears. It causes discomfort and could lead to severe visual problems. In this chapter, we explain how machine learning techniques can be applied in some DES medical tests in order to produce an objective, repeatable and automatic diagnosis. The results of our experiments show that the proposed methodologies behave like the experts so that they can be applied in the daily practice. © Springer International Publishing AG 2018. en
dc.identifier.uri en
dc.language eng en
dc.relation 6485 en
dc.rights info:eu-repo/semantics/embargoedAccess en
dc.title Machine Learning Applied to Optometry Data en
dc.type bookPart en
dc.type Publication en
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