Title: A K-means and fuzzy logic-based system for clinical diagnosis (staging) of cervical cancer

Authors: Oluwakemi Christiana Abikoye; Emmanuel Oluwaseun Olajide; Akinbowale Nathaniel Babatunde; Abimbola Ganiyat Akintola

Addresses: Department of Computer Science, University of Ilorin, Ilorin, Nigeria ' Department of Computer Science, University of Ilorin, Ilorin, Nigeria ' Department of Computer Science, Kwara State Universiy, Malete, Nigeria ' Department of Computer Science, University of Ilorin, Ilorin, Nigeria

Abstract: In cases of the burden arising from cancer world, cervical cancer is the most common type of gynaecological cancer, accounting 8% (527,624 cases in 2012) of all female malignancies, second only to breast and colorectal cancer. Women with cervical cancer constitute patient populations that are in need of ongoing, person-centred supportive care. The unavailability of technologies that can determine the stage of cervical cancer constitutes a problem in the actual diagnosis. Previously physician predict the cancer stage on the basis of their experience in the field, however this is prone to error because man's judgement are sometimes clouded by emotions. This research seeks to address this problem with the design of a k-means and fuzzy logic based system for clinical diagnosis (staging) of cervical cancer. The K-means algorithm was used for the grouping of data and fuzzy logic for the rule based prognosis of cervical cancer.

Keywords: cervical cancer; fuzzy logic; K-means; diagnosis; staging; algorithm; rule-based; prognosis.

DOI: 10.1504/IJTMCP.2017.083890

International Journal of Telemedicine and Clinical Practices, 2017 Vol.2 No.2, pp.168 - 196

Received: 28 Nov 2016
Accepted: 14 Dec 2016
Published online: 25 Apr 2017 *

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