Abstract
Glaucoma is one of the main causes of blindness in the world. Until it reaches an advanced stage, Glaucoma is asymptomatic, and an early diagnosis improves the quality of life of patients developing this illness.
In this paper we put forward an algorithmic solution for the diagnosis of Glaucoma. We approach the problem through a hybrid model of fuzzy and soft set based decision making techniques. Automated combination and analysis of information from structural and functional diagnostic techniques are used in order to obtain an enhanced Glaucoma detection in the clinic.
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Acknowledgments
Alcantud acknowledges financial support from the Spanish Ministerio de Economía y Competitividad (Project ECO2012–31933). The research of Santos-García was partially supported by the Spanish project Strongsoft TIN2012–39391–C04–04.
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Alcantud, J.C.R., Santos-García, G., Hernández-Galilea, E. (2015). Glaucoma Diagnosis: A Soft Set Based Decision Making Procedure. In: Puerta, J., et al. Advances in Artificial Intelligence. CAEPIA 2015. Lecture Notes in Computer Science(), vol 9422. Springer, Cham. https://doi.org/10.1007/978-3-319-24598-0_5
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