Secured Data Access for Alzheimer’s Patients Using Blockchain And Machine Learning: A Novel Approach
M. Diviya, Siva Sandeep Yenumula · 2025
Accessing and managing Alzheimer patient data provided by the patients themselves poses a challenge to both the research and healthcare community as it is necessary to protect the privacy of the patient. In this paper, we are proposing a decentralized, secure storage and access control system, based on smart contracts and Interplanetary File System (IPFS), that makes use of a blockchain based architecture. Access permissions are granted through the use of smart contracts ensuring that sensitive information is only accessed by approved parties. The patient’s data is kept off-chain using IPFS enhancing the efficiency and integrity of the data management. Additionally, there is an integrated model of machine learning, namely XGBoost, which is used to model and forecast the progression of Alzheimer disease with an aim of providing tailored medical insights. This technique is applied in providing enhanced security of the data and more advanced analytic insight into Alzheimer care.