Lung Cancer Prediction Model Using Machine Learning

Abstract

Lung cancer is one of the most widespread and life-threatening cancers across the world. A primary cause of this disease is cigarette smoking. It develops in the tissues of the lungs when cells begin to grow uncontrollably and abnormally. Lung cancer can originate in any part of the lungs and may impact the entire respiratory system. Therefore, early detection is crucial, and this can be achieved using various machine learning techniques. In this study, the KNearest Neighbors (KNN) algorithm is applied for lung cancer prediction. The model’s performance is evaluated using accuracy scores and a confusion matrix to distinguish between correct and incorrect predictions. The process involves importing a relevant dataset and applying machine learning algorithms to analyze the data, ultimately determining whether individuals are likely to be affected by lung cancer.