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Cancer, Cervical cancer, Decision tree Classifier, herpes virus, K-nearest neighbor, Machine learning, Random forest
Cervical Cancer is one of the main reason of deaths in countries having a low capita income. It becomes quite complicated while examining a patient on basis of the result obtained from various doctor’s preferred test for any automated system to determine if the patient is positive with the cancer. There were 898 new cases of cervical cancer diagnosed in Australia in 2014. The risk of a woman being diagnosed by age 85 is 1 in 167. We will try to use machine learning algorithms and determine if the patient has cancer based on numerous factors available in the dataset. Predicting the presence of cervical cancer can help the diagnosis process to start at an earlier stage.
Dhwaani Parikh, Vineet Menon,"Machine Learning Applied to Cervical Cancer Data", International Journal of Mathematical Sciences and Computing(IJMSC), Vol.5, No.1, pp.53-64, 2019. DOI: 10.5815/ijmsc.2019.01.05
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