Abstract
The fourth known cause of cancer death in females can be attributed to cervical cancer. Cervical cancer claims more than 26,500 lives per year. This indeed is a matter of concern for everyone of us. Like any other disease, the requirement for many tests and physician preferences makes this a complex system. Here we are trying to minimize that by taking a dataset of Hinselmann’s test and then using supervised machine learning and logistics regression to give a solid output on patient’s condition.
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Singh, S., Panday, S., Panday, M., Rautaray, S.S. (2019). Logistic Regression for the Diagnosis of Cervical Cancer. In: Shukla, R.K., Agrawal, J., Sharma, S., Singh Tomer, G. (eds) Data, Engineering and Applications. Springer, Singapore. https://doi.org/10.1007/978-981-13-6347-4_10
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DOI: https://doi.org/10.1007/978-981-13-6347-4_10
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