Abstract
In the last decades, the use of video display terminals in workplaces has become more and more common. Despite their remarkable advantages, they imply a series of risks for the health of the workers, as they can be responsible for ocular and visual disorders.
In this research, certain problems associated to prolonged computer use classified under the name of Computer Vision Syndrome are studied with the help of a hybrid algorithm based on regression trees and genetic algorithms. The importance of the different symptoms on the Computer Vision Syndrome is evaluated.
Also, the proposed algorithm is tested in order to know its performance as a prediction model that can determine how prone an individual is to suffering from Computer Vision Syndrome.
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Artime Ríos, E.M., Sánchez Lasheras, F., Suárez Sánchez, A., Iglesias-Rodríguez, F.J., Seguí Crespo, M.d.M. (2018). A Hybrid Algorithm for the Prediction of Computer Vision Syndrome in Health Personnel Based on Trees and Evolutionary Algorithms. In: de Cos Juez, F., et al. Hybrid Artificial Intelligent Systems. HAIS 2018. Lecture Notes in Computer Science(), vol 10870. Springer, Cham. https://doi.org/10.1007/978-3-319-92639-1_50
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