Abstract
In this paper the first results of the process of extracting survival patterns in diagnosed women with invasive cervical cancer with classification techniques from data reported in population-based cancer registry of the municipality of Pasto (Colombia) for a time period of 10 years are presented. The generated knowledge will allow to understand the different socioeconomic and clinical factors affecting the survival of this population group. This knowledge will support effective decision making of government agencies and private health sector in relation to the approach of public policies and prevention programs designed to detect new cases of women with this disease early.
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Timarán Pereira, R., Yepez Chamorro, M.C., Calderón Romero, A. (2012). Detecting Survival Patterns in Women with Invasive Cervical Cancer with Decision Trees. In: Pavón, J., Duque-Méndez, N.D., Fuentes-Fernández, R. (eds) Advances in Artificial Intelligence – IBERAMIA 2012. IBERAMIA 2012. Lecture Notes in Computer Science(), vol 7637. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34654-5_14
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DOI: https://doi.org/10.1007/978-3-642-34654-5_14
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