How Lung Cancer Severity Can Be Predicted Using Machine-Learning Based on Different Risk Factors

Lung cancer is among the top causes of death globally, so this study sought to create a medical diagnostic solution in surveying the relationships between features such as symptoms and risk factors for lung cancer severity. 1000 publicly-accessible, anonymized patient records, different machine learning models were utilized with classification accuracy ranging from 92.5 to 100%. These findings argue for a greater role of passive smoke exposure in lung cancer severity than previously established, though further research is encouraged.