Lung cancer is a major cause of death in Vietnam, with high disease rates and public health burden.
The study focuses on understanding the sources of lung cancer in Vietnam, considering environmental features, health state, and the country's socioeconomic and ecological context.
Large datasets, including patient health records and environmental indicators, are utilized to determine causal correlations and identify cancer risk patterns.
Machine learning models, such as Decision Tree, Random Forest, and Support Vector Machine, show promising results in identifying disease patterns with high accuracy.