Blockchain technology for smart cancer care

Abstract

Data security and privacy are very important in smart health applications. When the information security requirements of patients’ confidential data and these applications that process these data and obtain other private data are examined, it is seen that blockchain approaches have applications that are capable of meeting all of these requirements. In this context, in this study, first, current literature studies focused on smart health applications were examined. As a result of the examination, it was seen that most of the current applications offer approaches using blockchain and artificial intelligence (AI) technologies in smart health applications. Therefore, we first investigated the blockchain requirements of smart healthcare applications. We researched what types of problems blockchain is used to solve in smart healthcare applications in the literature. Within the scope of the study, various use case examples for smart health applications of blockchain were presented, including medical supply chain management, remote health monitoring, wearable health devices, and metaverse applications. As a result of our research, we proposed a new method for the integration of AI and blockchain technologies into smart healthcare applications. In the method we developed, we presented a new smart contract structure that automates patient, doctor, prescription, appointment, and insurance processes by performing anomaly classification of data received from wearable devices with deep learning models and according to this classification result. In order to present an example application with the approach we developed, we trained a CNN (Convolutional Neural Network) model that classifies the electrocardiography data of chronic heart patients. The test performance of the approach we developed has exceeded 97%. Then, we integrated the smart contract that manages the drug prescription update processes based on the results obtained from this model. As a result of the study, the automation of multiple medical processes was carried out in a safe, transparent, and efficient manner with the smart contract we proposed. Apart from our smart contract, the performance of our proposed electronic health record classification approach has also been proven with experimental results. © 2025 Elsevier Inc. All rights reserved.