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- W3135829120 abstract "Cervical cancer is a commonly occurring deadliest disease among women, which needs earlier diagnosis to reduce the prevalence. Pap-smear is considered as a widely employed technique to screen and diagnose cervical cancer. Since classical manual screening techniques are inefficient in the identification of cervical cancer, several research works have been started to develop automated machine learning (ML) and deep learning (DL) tools for cervical cancer diagnosis. This paper surveys the recent works made on cervical cancer diagnosis and classification. The recently presently ML and DL models for cervical cancer diagnosis and classification has been reviewed in detail. Besides, segmentation techniques developed for cervical cancer diagnosis also surveyed. At the end of the survey, a brief comparative study has been carried out to identify the significance of the reviewed methods." @default.
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- W3135829120 date "2020-12-01" @default.
- W3135829120 modified "2023-10-18" @default.
- W3135829120 title "An Extensive Review on Machine Learning and Deep Learning Based Cervical Cancer Diagnosis and Classification Models" @default.
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- W3135829120 doi "https://doi.org/10.1166/jctn.2020.9437" @default.
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