Research Article

A Federated Epidemiological Modelling Architecture Leveraging Cloud Technology and Blockchain for Cancer Cell Growth Management

Abstract

Cancer growth has a high correlation with the dynamic and complex changing interactions of malignant cells, different treatment responses and human immune systems. It is always difficult to make predictions and deliver timely and accurate prediction while also managing secure clinical data management. This novel study presents a federated architecture that assembles epidemiological modelling (Feedback-based SIR Model) along with cloud computing and blockchain technology. It also applies machine learning to improve the predictive capability of cancer cell growth along with managing clinical records. On top of that the framework applies blockchain technology with off-chain storage using the Inter Planetary File System (IPFS that ensures scalability, security and preserving & managing sensitive clinical records. Experimental assessment demonstrates that the feedback-based SIR model significantly surpasses conventional approaches SIR model in predictive accuracy and that the proposed blockchain – cloud architecture achieves an effective balance between security and system performance, providing a robust and scalable foundation for precision oncology, intelligent decision support and collaborative cancer research.