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A Model Framework for Cervical Lesions (CL) Screening Using Adaptive Neuro-fuzzy Inference Systems (ANFIS): A Study on Commercial Sex Workers (CSWs) Predict Diagnosis

Presentation Type: Oral 2016

Submission ID: 39 Name:Dr. B.E. Contact: ,
Contributing Authors: Odigie B.E. Achukwu P.U. Atoigwe B.E. Obaseki D.E. Usunobun J.O. Bello M.E. Odega K.I. Omorodion, N.T. and Odigie .JO.

Category: CMS
Faculty: Basic Medical Science
Department: Department of Medical Laboratory Sciences
Address: Sexual Health Concerns for Commercial Sex Workers (SHCCSW) Research Group-UNIBEN, Nigeria
Specialization:
Keywords: ANFIS, cervical lesions, commercial sex workers and liquid-based cytology
Submission date: 2018-08-29 21:10:49

Abstract

The commercial sex workers CSWs are group of women that gives sex in an exchange for monetary gains and use the illicit act as a major source of livelihood. They are increasingly at risk of acquiring infections, which could influence cervical lesions (CL) (Odigie and Achukwu, 2015). CL, however, is all pathological abnormalities seen in cells and/or tissues taken from the cervix (Obaseki and Nwafor, 2015). The current widely used methods [(Pap smear by Ayres spatula and the liquid based cytology (LBC)] for screening CL are time-consuming and dependent on the skill of the pathologist/ cytologist (Mohammad et al., 2014). These methods are invasive, which has led to the growing concerns for the formulation of a diagnostic model especially for the screening of CSWs who scarcely present in hospitals for checkup. From the foregoing, the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) could be used for CL screening in CSWs as pre-diagnosis. ANFIS is a hybrid system that comprises of Neural Network (NN) and Fuzzy Logic (FL).


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