Monday, 11 Dec, 2023




Machine Learning Approach for Cervical Cancer Prediction

International Journal of Emerging Trends in Science and Technology

Volume 8 Issue 1

Published: 2022
Author(s) Name: Dhivya, R. Dharani and R. Raja Guru | Author(s) Affiliation: M.Kumarasamy College of Engineering, Karur, Tamil Nadu, India.
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Women withinside the global are affected by many sicknesses amongst the ones sicknesses Cervical Cancer is likewise referred to globally. Every 12 months many most cancers instances are being registered for the duration of the global. Cervical most cancers is ranked fourth of all of the different not unusual place cancers consistent with WHO. Prediction of this most cancers in its early tiers may be cured, keeping off the demise price. Many human beings are much less privy to this sort of most cancers as this sickness is symptom much less. Performance of screening take a look at in ordinary bases cancerous cells may be detected in its early tiers which reduces the mortality price of human beings each 12 months. There are many scientific tactics for the prediction of this most cancers like pap-smear take a look at, colposcopy, biopsy, HPV take a look at or HPV DNA take a look at and different screening exams are performed. These scientific strategies are blended with the Artificial Intelligence for much less fake price and greater correct results. This paper considers pap-smear take a look at snap shots for the prediction of cancerous cells blended with Deep Learning strategies for greater green results. Convolution Neural Networks (CNN’s) ResNet50 pre-educated version for the prediction of cancerous cells which produces correct results. The proposed paintings classify the cells from the inputted snap shots. This most cancers may be cured while its far with inside the preliminary tiers, the diagnosed ordinary cells allows us for the similarly treatment. The proposed method classifies all of the instructions with 74.04 percent of accuracy in prediction of cells for max wide variety of epochs. Also in addition, it specifies the elegance of the trying out image.

Keywords: Deep Learning, Convolution Neural Network, ResNet50, Transfer Learning, Cancer of Cervix, Pap-Smear snap shots

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