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.
CITATION STYLE
Alcantud, J. C. R., Santos-García, G., & Hernández-Galilea, E. (2015). Glaucoma diagnosis: A soft set based decision making procedure. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9422, pp. 49–60). Springer Verlag. https://doi.org/10.1007/978-3-319-24598-0_5
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