Applied data mining patterns to discovery survival in women with invasive cervical cancer

Abstract

In this paper the results of rhe research project whose goal was to extract survival patterns in diagnosed women with invasive cervical cancer with data mining techniques from data reported in Population-based Cancer Registry of the Municipality of Pasto (Colombia), during a period between 1998 and 2007 are presented. According ti the results, which were obtained by applying the classification technique based on decision trees, the survival time of these women is greater than 37 months, counted from the date of diagnosis to the last date of observation of the present study. By applying the Association task, the main socioeconomic and clinical factors associated with survival of this population group were met. The generated knowledge will support effective decision making of government agencies and private health sector in relation to the approach of public policies and protection programs for women with this disease.