A Prediction Model for Lung Cancer Levels Based on Machine Learning

Huu-Huy Ngo, Hung Linh Le

Abstract


Among cancers, lung cancer is one of the most dreaded conditions, and it is the leading cause of cancer-related deaths worldwide. Early cancer identification and prediction help prevent and treat cancer efficiently, especially the beginning cancer stage. Therefore, this study presents a prediction model for lung cancer level based on machine learning. Machine learning algorithms are applied as primary methods. Firstly, the dataset collection is implemented; then, feature selection algorithms are used to identify essential features. Secondly, the proposed model applies the machine learning algorithms on two datasets (The full dataset and the dataset of essential features). Finally, experimental results demonstrate that this proposed system has an excellent performance, with 100% and 98.7% accuracy on the full dataset and the dataset of the top three essential features, respectively.

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References


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