Adaptive Neuro Fuzzy Inference System (ANFIS) Based Detection of Cervical Cancer.
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Date
2018-11-22
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Published by LAUTECH, Ogbomoso. Oyo State
Abstract
Cancer occurs when cells in an area of the body grows abnormally. Cervical cancer is a cancer that is known to be the second most deadly cancer affecting women worldwide which emerges from the cervix of a woman. The normal cervix has two main types of cells: squamous cells, that protect the outside of the cervix and glandular cells. Cervical cancer is caused by abnormal changes in either of these cell types in the cervix. Pap smear screening is the most successful attempt of medical science and practice for the early detection of cervical cancer. However, the manual analysis of the cervical cells (pap smear) is time consuming, laborious and error prone.
In this research, detection of cervical cancer was done using Adaptive Neuro-Fuzzy Inference System (ANFIS), a hybrid intelligent system which combines the fuzzy logic qualitative approach and adaptive neural network capabilities. The system was modelled to predict the probability of cervical cancer as either high probability or low probability based on the input risk factors of cervical cancer as contained in the dataset used.
The efficiency of the ANFIS in predicting cervical cancer was tested using a dataset collected from Leah Foundation, a non-governmental organization in Nigeria, having a total of 250 patient’s data. The dataset contains eight risk factors of cervical cancer, which serves as the input variables. The output is the classified risk factors each patient is prone to. A patient with low level (represented as 1) is classified to be of no or less probability of having cervical cancer, while a patient with high level (represented as 2) is classified to be a victim of high probability of having cervical cancer.
The result of this system shows that the system can be adopted by medical practitioners as well as for individual use.
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Babatunde, R. S. and Muhammad-Thani S. (2018):