Classification of cervical cancer using machine learning techniques: a review Online publication date: Wed, 01-Mar-2023
by Sanat Jain; Ashish Jain; Mahesh Jangid
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 18, No. 6, 2022
Abstract: One of the most prevalent and deadliest malignancies in women is cervical malignancy. It is the fourth major cause of death among women worldwide. Women's lives can be saved if this malignancy is identified at a precancerous stage because it is fully curable at an early stage. The most widely used screening procedure for cervical malignancy is the pap test. As a result, computerised identification and classification of cervical malignancy from pap images have become essential because they provide a precise, reliable, and fast investigation of the disease's progress. This paper provides a comprehensive overview of the automatic identification of cervical malignancy, its causes, risk factors, and symptoms. This paper also discusses the following: the pap test, which is widely used in screening, the computer-aided diagnosis requirement for the classification of cervical cells, the classes of cervical cells for segmentation as well as classification, and the existing techniques for classifying cervical cells.
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