Enhancing cervical cancer diagnosis with graph convolution network: AI-powered segmentation, feature analysis, and classification for early detection
Nur Mohammad Fahad,
Sami Azam,
Sidratul Montaha
et al.
Abstract:Cervical cancer is a prevalent disease affecting the cervix cells in women and is one of the leading causes of mortality for women globally. The Pap smear test determines the risk of cervical cancer by detecting abnormal cervix cells. Early detection and diagnosis of this cancer can effectively increase the patient’s survival rate. The advent of artificial intelligence facilitates the development of automated computer-assisted cervical cancer diagnostic systems, which are widely used to enhance cancer screenin… Show more
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