An High Accuracy Lung Cancer Detection System Using MRMR Method

Abstract

Lung cancer is one of the main cause of the death and health issue in many countries with 5-year survival rate of only10–16%. In this project we use machine learning algorithms to diagnose a cancer and start treatment in early stages. MRMR method and decision tree algorithms to predict the high accuracy of the cancer. In this project we use scikit-learn libraries like sklearn and pandas to predict and classify the dataset of the lung cancer patients. Slicing the dataset and feature scaling options are used to train the dataset. After that we use confusion matrix , f1 score and accuracy score to predict the accuracy of the result.Success obtained was 99.51% with 200 features provided by MRMR. In the dataset lung cancer.csv the result attributes which have 0 value which represent person have no lung cancer and 1 value represents person have lung cancer. These researchers then performed the 10- fold cross-validation for model evaluation.IOT arduino UNO is interfaced with WIFI module to collect the data. wifi sensor is connected with various IOT sensor to obtain the information of the patient like temp, BP, Pulse rate..Using wifi module patient data is transfer to doctor to protect the patient in early stages.