相关论文: Multi-MedChain: Multi-Party Multi-Blockchain Medic…
This paper addresses the critical challenge of ensuring healthcare policy compliance in the context of Electronic Health Records (EHRs). Despite stringent regulations like HIPAA, significant gaps in policy compliance often remain undetected…
The digital transformation of the medical sector requires solutions that are convenient and efficient for all stakeholders while protecting patients' sensitive data. One example that has already attracted design-oriented research are…
Protected Health Information (PHI) sharing significantly enhances patient care quality and coordination, contributing to more accurate diagnoses, efficient treatment plans, and a comprehensive understanding of patient history. Compliance…
Integrating on-chain and off-chain data storage for decentralised and distributed information systems, such as blockchain, presents specific challenges for providing transparency of data governance and ensuring data integrity through…
Several problems in healthcare stem from the complex network of intermediaries and the lack of traceability of transactions. To mention a few: healthcare data is fragmented across several silos negatively affecting research and services,…
Usually, a medical record (MR) contains the patients disease-oriented sensitive information. In addition, the MR needs to be shared among different bodies, e.g., diagnostic centres, hospitals, physicians, etc. Hence, retaining the privacy…
This research explores the integration of blockchain technology in healthcare, focusing on enhancing the security and efficiency of Electronic Health Record (EHR) management. We propose a novel Ethereum-based system that empowers patients…
No one can dispute the disruptive impact of blockchain technology, which has long been considered one of the major revolutions of contemporary times. Its integration into the healthcare ecosystem has helped overcome numerous difficulties…
The financial sustainability of a generic supply chain is a complex problem, which can be addressed through detailed monitoring of financial operations deriving from stakeholder interrelationships and consequent analysis of these financial…
Electronic medical data sharing between stakeholders, such as patients, doctors, and researchers, can promote more effective medical treatment collaboratively. These sensitive and private data should only be accessed by authorized users.…
Health data is a sensitive category of personal data. It might result in a high risk to individual and health information handling rights and opportunities unless there is a palatable defense. Reasonable security standards are needed to…
The imbalance between the supply and demand of healthcare resources is a global challenge, which is particularly severe in developing countries. Governments and academic communities have made various efforts to increase healthcare supply…
The design of access control mechanisms for healthcare systems is challenging: it must strike the right balance between permissions and restrictions. In this work, we propose a novel approach that is based on the Blockchain technology for…
Traceability and integrity are major challenges for the increasingly complex supply chains of today's world. Although blockchain technology has the potential to address these challenges through providing a tamper-proof audit trail of supply…
The emergence of the Internet of Things (IoT) has resulted in a significant increase in research on e-health. As the amount of patient data grows, it has become increasingly challenging to protect patients' privacy. Patient data is commonly…
Timely sharing of electronic health records (EHR) across providers is essential and significance in facilitating medical researches and prompt patients' care. With sharing, it is crucial that patients can control who can access their data…
Healthcare data is sensitive and requires great protection. Encrypted electronic health records (EHRs) contain personal and sensitive data such as names and addresses. Having access to patient data benefits all of them. This paper proposes…
Large-scale computational experiments, often running over weeks and over large datasets, are used extensively in fields such as epidemiology, meteorology, computational biology, and healthcare to understand phenomena, and design high-stakes…
COVID-19 is a severe global epidemic in human history. Even though there are particular medications and vaccines to curb the epidemic, tracing and isolating the infection source is the best option to slow the virus spread and reduce…
Cross-institutional healthcare predictive modeling can accelerate research and facilitate quality improvement initiatives, and thus is important for national healthcare delivery priorities. For example, a model that predicts risk of…