Women Healthcare Mobile App-An Approach to Predict Early Stage of Cervical Cancer

Abstract

Most of the woman nowadays is ending up their life at middle age between 35-50 years, reason they are suffering from Cervical related cancer tumours. Many women are unaware of having cervical related cyst in the early stages. A survey was conducted on classifiers such as Decision Tree, Multilayer Perceptron, and Nave Bayes, with True Positive Rate, False Positive Rate, Precision, and Recall being measured, and an Android Mobile App was built to forecast the risk of having a Cervical associated cyst in its early stages. For training and testing the classifiers, we have used cervical dataset from University of California at Irvine Machine Learning Repository. Cervical Dataset consists of 858 records containing 32 attribute values and 4 diagnosis class value. For Cervical cancer prediction only 21 attributes and 1 biopsy class value is considered. The proposed Android Mobile App capable of predicting risk of a woman is affected by cervical related cyst in early stages. A normal woman can identify chances of having Cervical Cancer at finger tips with the proposed Android Mobile App.