A Comprehensive Review on Analysis of Cervical Cancer Diagnostic Techniques
DOI:
https://doi.org/10.17762/msea.v71i3.253Abstract
Cervical cancer (CC) in women among the ages of 18 and 60. Cervical cancer refers to the unrestrainedexpansion of abnormal cells in the cervix area. It is very problematic to detect and classify the CC. Because it occurs without any symptoms in the early stages. However, early detection of CC/pre-cancer can improve patient survival rates. This disease was diagnosed, using both manual and automatic detection methods. Compared with manual detection approachessuch as the pap-smear test and the LCB test, classification of normal, precancerous and cancer cells using a Convolutional Neural Network (which combines feature classification) with Deep Learning algorithms produces more accurate results. This paper examines the application of various algorithms indiagnosis of CC as well as their accuracy and performance measurement.