Deep Learning-Based Technique for The Perception of The Cervical Cancer

In third-world countries, cervical cancer is the most prevalent and leading cause of death. It affected by a variety factors, including smoking, poor nutritional status, immunological inadequacy, prolonged use contraception. The Pap smear test, which intended to prevent cancer, finds preneoplastic changes in epithelial cells. This study framework classified cells from smears into five specified cell types using machine learning-based classification algorithms. SIPaKMeD database used this investigation. public dataset, was manually cropped 966 cluster images taken slides, has 4045 isolated Depending on their cellular form structure, experts categorize distinct are superficial-intermediate, Parabasal, Koilocytotic, Dyskeratotic, Metaplastic Introducing pipeline improve algorithm accuracy easy implementation feature extractor conducting suitable preprocessing main contribution. reached conclusion that learning could screening results. We concluded support vector (SVM) for application. SVM highest 0.968, Neural Network (NN) at 0.958, (K-Nearest Neighbor) KNN 0.941. These results proposed as reliable diagnostic tool.