ABSTRACT
One of the most common illnesses affecting women is cervical cancer, which may be prevented with an early diagnosis. While there are currently relatively little medical resources available for prevention, identification, and treatment, the incidence rates of cervical cancer in poor nations have been sharply rising. Rapid and very accurate cancer screening can be achieved with the computer-based deep learning technology. This approach may result in an early detection of cervical cancer, efficient treatment, and ultimately successful prevention. Cervical cell screening using traditional means is primarily dependent on the experience of pathologists and is associated with low efficiency and accuracy. Deep learning and machine learning combined with medical image processing demonstrates its advantage in cell classification. A revised framework founded on strong feature Convolution Neural Networks (CNN)-Support Vector Machine (SVM) model was proposed to accurately classify the diseases.
