vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff03d82b000000a121060001000c00 Cervical cancer is regarded as a serious threats to humanity, globally and this is a vital disease with huge spreading of virus that affects the health of humans. The virus is spreading at a rapid rate through mosquitoes that even may kill the one who is affected with cervical cancer. In this paper, we develop a quick response system that certainly finds the disease through a faster validation process. The study uses Deep Neural Network (DNN) as a deep learning model that classifies and predicts the condition or the infection status of a patient. The study uses a pre-processing model and a feature extraction model to prepare the image datasets for classification. The simulation is conducted to validate the effectiveness of the model over cervical cancer image datasets i.e. the blood samples of humans. The validation shows that the proposed method effectively classifies the patients in a faster manner than the other deep learning models.
M Ramkumar1, R Manikandan2, M Punithavalli3, V S Akshaya4, Shanmugaraj Madasamy5
Gnanamani College of Technology, India1, The Quaide Milleth College for Men, India2, Rathinam Technical Campus, India3, Sri Eshwar College of Engineering, India4, Cork Institute of Technology, Ireland5
Machine Learning, Cervical cancer, Classification, Diagnosis
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| Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 11 , Issue: 4 , Pages: 2470-2474 )
Date of Publication :
May 2021
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585
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