Detecting Survival Patterns in Women with Invasive Cervical Cancer with Decision Trees

  • Ricardo Timarán Pereira
  • Maria Clara Yepez Chamorro
  • Andrés Calderón Romero
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7637)

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.

Keywords

survival patterns invasive cervical cancer data mining classification task 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ricardo Timarán Pereira
    • 1
  • Maria Clara Yepez Chamorro
    • 2
  • Andrés Calderón Romero
    • 1
  1. 1.Facultad de Ingeniería, Departamento de SistemasUniversidad de NariñoSan Juan de PastoColombia
  2. 2.Centro de Estudios en SaludUniversidad de NariñoSan Juan de PastoColombia

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