Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Feb 21, 2019
Open Peer Review Period: Feb 22, 2019 - Apr 19, 2019
Date Accepted: Jun 20, 2019
(closed for review but you can still tweet)
Cloud health resource sharing based on consensus-oriented blockchain technology: A case study on breast tumor diagnosis service
ABSTRACT
Background:
In recent years, an increasing number of researchers have made significant effort in advancing the blockchain technology. This technology, with distinct features of decentralization and security, can be applied to many fields. On the aspects of health data and resource sharing, the application blockchain technology is emerging.
Objective:
In this study, we propose a cloud health resource sharing model based on consensus-oriented blockchain technology and develop a simulation study on the service of breast tumor diagnosis.
Methods:
The proposed platform is built on a consortium or federated blockchain which possesses the features of both centralization and decentralization. The consensus mechanisms generate the operating standards for the proposed model. The open source Ethereum code is employed to provide the blockchain environment. Proof-of-Authority (PoA) is selected as the consensus algorithm of block generation.
Results:
Based on the proposed model, a simulation case study for breast tumor classification is constructed. The simulation includes 9893 service requests from 100 users. 22 service providers are equipped with 22 different classification methods, respectively. Each request is fulfilled by a service provider which is recommended by the weighted k-nearest neighbors (KNN) algorithm. It is shown that the majority of service requests tend to be taken by 9 providers and the provider’s score of service evaluation tends to be stabilize. Also, the user priority on KNN weights significantly affects the system operation outcome.
Conclusions:
The proposed model is feasible based on the simulation case study for the cloud service of breast tumor diagnosis and has potential to be applied to many other purposes.
Citation
Per the author's request the PDF is not available.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.