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Neural Computing and Applications
Published in: Neural Computing and Applications 5/2020

06-06-2018 | S.I. : AI and ML applied to Health Sciences (MLHS)

Genetic algorithm based on support vector machines for computer vision syndrome classification in health personnel

Authors: Eva María Artime Ríos, Ana Suárez Sánchez, Fernando Sánchez Lasheras, María del Mar Seguí Crespo

Published in: Neural Computing and Applications | Issue 5/2020

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Abstract

The inclusion in workplaces of video display terminals has brought multiple benefits for the organization of work. Nevertheless, it also implies a series of risks for the health of the workers, since it can cause ocular and visual disorders, among others. In this research, a group of eye and vision-related problems associated with prolonged computer use (known as computer vision syndrome) are studied. The aim is to select the characteristics of the subject that are most relevant for the occurrence of this syndrome, and then, to develop a classification model for its prediction. The estimate of this problem is made by means of support vector machines for classification. This machine learning technique will be trained with the support of a genetic algorithm. This provides the training of the support vector machine with different patterns of parameters, improving its performance. The model performance is verified in terms of the area under the ROC curve, which leads to a model with high accuracy in the classification of the syndrome.
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Metadata
Title
Genetic algorithm based on support vector machines for computer vision syndrome classification in health personnel
Authors
Eva María Artime Ríos
Ana Suárez Sánchez
Fernando Sánchez Lasheras
María del Mar Seguí Crespo
Publication date
06-06-2018
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 5/2020
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3581-3

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