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| Format: | Artículo científico |
| Language: | en |
| Published: |
Asociación Española para la Inteligencia Artificial
2005
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| Online Access: | https://www.redalyc.org/articulo.oa?id=92526903 |
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Table of Contents:
- A hybrid visual field classifier to support early glaucoma diagnosis Ma. Aránzazu Simón Luis Alonso Alfonso Antón Ingeniería Self Expert System Hybrid Classifier Glaucoma Diagnosis Organizing Map (SOM) Primary Open Angle Glaucoma is an eye disease that can, eventually, cause irreversible damage to theoptic nerve. Because of this an accurate diagnosis at early stages of the disease is necessary to stop ordelay its progression. Perimetry, one of the most important tests to detect glaucoma, gives a large amountof numerical data that is difficult to analyze. A number of approaches are described in the literature toovercome this problem, some of them using artificial neural networks, mainly MLP with BP. In this paper, aHybrid Visual Field Classifier System is proposed, comprising a Self-Organizing Map (SOM) and a rule basedexpert system, integrating the knowledge that the SOM discovers with the expertise of the ophthalmologist.With this association, individual results of each component are improved up to a diagnostic precision of97%. 2005 artículo científico 1137-3601 https://www.redalyc.org/articulo.oa?id=92526903 en http://www.redalyc.org/revista.oa?id=925 Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial application/pdf Asociación Española para la Inteligencia Artificial Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial (España) Num.26 Vol.9