As the development of machine learning and deep learning, more and more people or organizations use multiple algorithms to analyse large collections of data to produce meaningful results that help to predict behaviour. And this kind of technology is increasingly used in medical field to predict some severe illness in their early stage, for example, cervical cancer. Cervical Cancer is one of the main reasons of deaths in countries having a low capita income. It is the second most common cancer in India in women accounting for 22.86% of all cancer cases in women. It becomes quite complicated while examining a patient on the basis of result obtained from various doctor’s preferred test to determine if the patient is positive with the cancer. There were 96,922 new cases of cervical cancer diagnosed in India in 2018. Around the globe, around a quarter of million people die owing to cervical cancer. Screening and different deterministic tests confuse the available Computed Aided Diagnosis (CAD) to treat the patient correctly for the cancer. Machine learning and Deep learning algorithms are used in this project and determine if the patient has cancer based on the analyses of the risk factors available in the dataset. Predicting the presence of cervical cancer can help the diagnosis process to start at an early stage and comparing various models will help in finding out the best prediction model for predicting the presence of cervical cancer effectively.
Cervical Cancer, Machine learning, Deep learning, Logistic regression, SVM, Decision Tree, Random Forest, Deep Neural networks, Dataset
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