Unraveling the Potential of Machine Learning in Lung Cancer Prediction

Lung cancer is a disease in which some undesired cells grow inside the lungs and as they grow older they get transferred to nearby lymph nodes and then to different parts of the body. Lung cancer is a very common disease that affects people of all ages. Its causes can be many either due to smoking or peer pressure. Cancer is a type of disease that spreads very fast in different parts of the body but cannot be easily identified. There are various researches previously done but the model on which they are trained is not giving much accurate results. There are different Machine Learning models used to predict lung cancer such as Tree, Random Forest, and Neural Network. The Neural Network was one of the supervised learning models which provided us with the most accuracy and precision. The best fit is calculated by the Area under Curve, Classification Accuracy, Precision, Fl Score, and Recall. In this discussion, it is all about various Machine Learning techniques, Orange software used for data prediction, and Tableau software used for Data visualization are done. The model is trained on the dataset of 310 rows and 16 columns. The value of each columns decides how will are model behave for different unknown values. The results of the model are also shown, including its accuracy, and the results are visualized through graphs that help to predict the disease which is better than all the existing model's results. It will let the readers be able to understand lung cancer more accurately and what data to include to get the most accurate results for lung cancer prediction.