Lung Cancer Risk Analysis and Prediction Using Machine Learning Techniques
DOI:
https://doi.org/10.54097/hset.v39i.6525Keywords:
Lang Cancer; Random Forest; Logistic Regression; Machine Learning.Abstract
In this work, the main challenges are to find the factors for lung cancer and to use machine learning techniques to analyze the risk of lung cancer. Lung cancer is a malignant tumor, usually arising from the bronchial mucosa or glands of the lungs. The death rate of patients is very rapid. The incidence and death rates of lung cancer are increasing year by year in many countries. Over the past 50 years, many countries have reported significant increases in lung cancer morbidity and mortality. The incidence and mortality of lung cancer in men rank first among all malignant tumors, and the incidence and mortality in women rank second. The random forest and logistic regression are used to predict lung cancer risk based on patients' symptomatic and behavioral features.
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