Characterizing the survival of women with invasive cervical cancer by using data mining

In this paper, one of the results of the research project entitled: Detection of survival patterns in diagnosed women with invasive cervical cancer with data mining techniques, using as the main source the information stored in the database of Cancer Registry of the Municipality of Pasto (Colombia) is presented here. Applying the CRISP-DM methodology, a data repository with information from diagnosed women with invasive cervical cancer during the period between 1998 and 2002 with an observation window until 2007, was built, cleaned, and transformed. The main socioeconomic and clinical factors related to survival of this population group, using classification, association, and clustering tasks were detected. The principal pattern discovered was that if a woman exceeds 52 months after the time of diagnosis of invasive cervical cancer, she will be characterized as a cancer survivor. 

• Tipo de recurso: http://purl.org/coar/resource_type/c_6511
• Fecha de publicación: 2016
• Institución: Universidad Pedagógica y Tecnológica de Colombia
• Repositorio: RiUPTC: Repositorio Institucional UPTC
• Idioma: spa
• OAI Identifier: oai:repositorio.uptc.edu.co:001/10219
• Acceso en línea: https://revistas.uptc.edu.co/index.php/investigacion_duitama/article/view/4315; https://repositorio.uptc.edu.co/handle/001/10219
• Palabra clave: cervical cancer; CRISP-DM; survival patterns; data mining.; cáncer de cuello uterino; CRISP-DM; patrones de supervivencia; minería de datos.
• License: Derechos de autor 2016 REVISTA DE INVESTIGACIÓN, DESARROLLO E INNOVACIÓN