Lung Cancer Detection using Machine Learning Algorithms and Neural Network on a Conducted Survey Dataset Lung Cancer Detection

Lung cancer is the expansion of malignant
cells in the lungs. Due to the rising frequency of cancer,
both the death rate for men and women has increased.
Lung cancer is a condition in which lung cells proliferate
uncontrolled. Although lung cancer cannot be averted,
the risk can be decreased. Therefore, early identification
of lung cancer is essential for improving patient survival.
Lung cancer incidence is directly inversely correlated
with the frequency of heavy smokers. Various
classification techniques, including Naive Bayes, Random
forest, Logistic Regression, Knn, Kernal svm and
Artificial neural network were used to investigate the
lung cancer prediction. The primary goal of this study is
to investigate the effectiveness of classification algorithms
and neaural network in the early identification of lung
cancer.