LUNG CANCER PREDICTION USING PREDICTIVE ANALYTICS

Abstract

Cancer is one of the most dangerous disease that involves unstoppable cell growth to all parts of the body .
Lung Cancer is known to be the most highest killer among all type of cancers such as Skin Cancer,Breast Cancer etc.
Lung Cancer is also called as Lung Carcinoma, which is a Malignant Tumor described by uncontrolled cell growth in
tissues of the Lung . To prevent lung cancer deaths,high risk individuals are screened with low-dose CT scans,because
early prediction will double the survival rate of the cancer patients. Usually Lung Cancer is predicted by using MRI (
Magnetic Resonance Imaging)scans and CT ( Computer Tomography) scans. We proposed a new model to predict
Lung Cancer by using textual data. In particular, we investigated about sex,age,Smoking habit,Alcohol consumption,
continuous Coughing, Wheezing trouble etc,. In this work,we use Supervised Machine Learning algorithms such as
Naive Bayes and Logistic Regression to predict Lung Cancer in terms of accuracy. Aim of our project is to build a
model for early prediction of the Lung Cancer which will help the doctor in saving the life of patients.