Abstract
The possibility of developing systems to support medical diagnosis through Artificial Intelligence (AI) allows conceiving Expert Systems (ES), which constitute successful methods to solve AI problems to program intelligent sys- tems. This work deals with creating an ES to support the diagnosis of cervical lesions by identifying them in colposcopic images; for this purpose, 140 images were analyzed, with the most interesting and relevant result from this action being the definition of discriminating features: surface, color, texture and edges. These features will be used to evaluate an image and offer diagnosis as established by the expert physician, like: normal, inflammation process, immature metaplasia, gland eversion and low-grade lesion. To evaluate the system’s performance, we obtained support from an expert colposcopy physician, who evaluated all 140 images. The results indicated that the ES obtained an efficiency of 75.75 % and an error percentage of 20.405%, including 4.04% that was not evaluated by the expert, who declared that the region or lesion was impossible to identify because the image was not clear.
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Abundez Barrera, I., Rendón Lara, E., Gutiérrez Estrada, C., Díaz Zagal, S. (2010). Diagnosis of Medical Images Using an Expert System. In: Kuri-Morales, A., Simari, G.R. (eds) Advances in Artificial Intelligence – IBERAMIA 2010. IBERAMIA 2010. Lecture Notes in Computer Science(), vol 6433. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16952-6_15
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DOI: https://doi.org/10.1007/978-3-642-16952-6_15
Publisher Name: Springer, Berlin, Heidelberg
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