7,691 research outputs found
Dwarna : a blockchain solution for dynamic consent in biobanking
Dynamic consent aims to empower research partners and facilitate active participation in the research process. Used within
the context of biobanking, it gives individuals access to information and control to determine how and where their
biospecimens and data should be used. We present Dwarna—a web portal for ‘dynamic consent’ that acts as a hub
connecting the different stakeholders of the Malta Biobank: biobank managers, researchers, research partners, and the
general public. The portal stores research partners’ consent in a blockchain to create an immutable audit trail of research
partners’ consent changes. Dwarna’s structure also presents a solution to the European Union’s General Data Protection
Regulation’s right to erasure—a right that is seemingly incompatible with the blockchain model. Dwarna’s transparent
structure increases trustworthiness in the biobanking process by giving research partners more control over which research
studies they participate in, by facilitating the withdrawal of consent and by making it possible to request that the biospecimen
and associated data are destroyed.peer-reviewe
The Serums Tool-Chain:Ensuring Security and Privacy of Medical Data in Smart Patient-Centric Healthcare Systems
Digital technology is permeating all aspects of human society and life. This leads to humans becoming highly dependent on digital devices, including upon digital: assistance, intelligence, and decisions. A major concern of this digital dependence is the lack of human oversight or intervention in many of the ways humans use this technology. This dependence and reliance on digital technology raises concerns in how humans trust such systems, and how to ensure digital technology behaves appropriately. This works considers recent developments and projects that combine digital technology and artificial intelligence with human society. The focus is on critical scenarios where failure of digital technology can lead to significant harm or even death. We explore how to build trust for users of digital technology in such scenarios and considering many different challenges for digital technology. The approaches applied and proposed here address user trust along many dimensions and aim to build collaborative and empowering use of digital technologies in critical aspects of human society
Secure and Trustable Electronic Medical Records Sharing using Blockchain
Electronic medical records (EMRs) are critical, highly sensitive private
information in healthcare, and need to be frequently shared among peers.
Blockchain provides a shared, immutable and transparent history of all the
transactions to build applications with trust, accountability and transparency.
This provides a unique opportunity to develop a secure and trustable EMR data
management and sharing system using blockchain. In this paper, we present our
perspectives on blockchain based healthcare data management, in particular, for
EMR data sharing between healthcare providers and for research studies. We
propose a framework on managing and sharing EMR data for cancer patient care.
In collaboration with Stony Brook University Hospital, we implemented our
framework in a prototype that ensures privacy, security, availability, and
fine-grained access control over EMR data. The proposed work can significantly
reduce the turnaround time for EMR sharing, improve decision making for medical
care, and reduce the overall costComment: AMIA 2017 Annual Symposium Proceeding
Blockchain technologies in healthcare institutions : focus on security and effective cooperation with the government
Purpose: This article considers the relevance of healthcare modernization processes in Russia in terms of marketing activities activation, public-private partnerships intensification. Design/Methodology/Approach: The problem of ensuring security when government and healthcare institutions interact by means of blockchain technologies is under-explored and requires further research and investigation. Therefore, methods of induction, deduction, problem, system and logical analysis along with the economic process and system modelling method combined with the formalization method are used in this article.
Findings: A mechanism for effective ensuring the safety of interaction between the government and healthcare institutions using blockchain technologies in the course of conducting financial flows and operational information exchange in modern Russia is proposed. Practical Implications: The proposed mechanism for effective ensuring of security in terms of interaction between the government and the healthcare institution by means of blockchain technologies in modern Russia effectively ensures the security of interaction between the government and healthcare institutions . Originality/Value: Authors’ findings could be introduced into the healthcare industry.peer-reviewe
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Privacy-preserving model learning on a blockchain network-of-networks.
ObjectiveTo facilitate clinical/genomic/biomedical research, constructing generalizable predictive models using cross-institutional methods while protecting privacy is imperative. However, state-of-the-art methods assume a "flattened" topology, while real-world research networks may consist of "network-of-networks" which can imply practical issues including training on small data for rare diseases/conditions, prioritizing locally trained models, and maintaining models for each level of the hierarchy. In this study, we focus on developing a hierarchical approach to inherit the benefits of the privacy-preserving methods, retain the advantages of adopting blockchain, and address practical concerns on a research network-of-networks.Materials and methodsWe propose a framework to combine level-wise model learning, blockchain-based model dissemination, and a novel hierarchical consensus algorithm for model ensemble. We developed an example implementation HierarchicalChain (hierarchical privacy-preserving modeling on blockchain), evaluated it on 3 healthcare/genomic datasets, as well as compared its predictive correctness, learning iteration, and execution time with a state-of-the-art method designed for flattened network topology.ResultsHierarchicalChain improves the predictive correctness for small training datasets and provides comparable correctness results with the competing method with higher learning iteration and similar per-iteration execution time, inherits the benefits of the privacy-preserving learning and advantages of blockchain technology, and immutable records models for each level.DiscussionHierarchicalChain is independent of the core privacy-preserving learning method, as well as of the underlying blockchain platform. Further studies are warranted for various types of network topology, complex data, and privacy concerns.ConclusionWe demonstrated the potential of utilizing the information from the hierarchical network-of-networks topology to improve prediction
RoboChain: A Secure Data-Sharing Framework for Human-Robot Interaction
Robots have potential to revolutionize the way we interact with the world
around us. One of their largest potentials is in the domain of mobile health
where they can be used to facilitate clinical interventions. However, to
accomplish this, robots need to have access to our private data in order to
learn from these data and improve their interaction capabilities. Furthermore,
to enhance this learning process, the knowledge sharing among multiple robot
units is the natural step forward. However, to date, there is no
well-established framework which allows for such data sharing while preserving
the privacy of the users (e.g., the hospital patients). To this end, we
introduce RoboChain - the first learning framework for secure, decentralized
and computationally efficient data and model sharing among multiple robot units
installed at multiple sites (e.g., hospitals). RoboChain builds upon and
combines the latest advances in open data access and blockchain technologies,
as well as machine learning. We illustrate this framework using the example of
a clinical intervention conducted in a private network of hospitals.
Specifically, we lay down the system architecture that allows multiple robot
units, conducting the interventions at different hospitals, to perform
efficient learning without compromising the data privacy.Comment: 7 pages, 6 figure
New Trends in Development of Services in the Modern Economy
The services sector strategic development unites a multitude of economic and managerial aspects and is one of the most important problems of economic management. Many researches devoted to this industry study are available. Most of them are performed in the traditional aspect of the voluminous calendar approach to strategic management, characteristic of the national scientific school. Such an approach seems archaic, forming false strategic benchmarks.
The services sector is of special scientific interest in this context due to the fact that the social production structure to the services development model attraction in many countries suggests transition to postindustrial economy type where the services sector is a system-supporting sector of the economy. Actively influencing the economy, the services sector in the developed countries dominates in the GDP formation, primary capital accumulation, labor, households final consumption and, finally, citizens comfort of living.
However, a clear understanding of the services sector as a hyper-sector permeating all spheres of human activity has not yet been fully developed, although interest in this issue continues to grow among many authors.
Target of strategic management of the industry development setting requires substantive content and the services sector target value assessment
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