ISI Journals

Cancer prevention remains a critical goal in public health, necessitating innovative approaches to improve prediction and intervention strategies. This article explores the integration of finite-volume methods and time series analysis to enhance cancer prevention efforts. Finite-volume methods, widely used in engineering, provide a robust framework for modeling the spatial-temporal dynamics of tumor growth. Time series analysis, commonly used in statistical forecasting, enables the identification of trends and patterns in cancer incidence over time. By combining these methodologies, this study aims to develop a comprehensive model for predicting cancer trends and informing prevention strategies. The results from a case study demonstrate the potential of this integrated approach to improve the accuracy and effectiveness of cancer prevention.