ArticleScientific reports2024
Integrating blockchain and ZK-ROLLUP for efficient healthcare data privacy protection system via IPFS.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Secure, scalable, and interoperable healthcare data exchange using layer-2 ZK-rollups, smart contracts, and IPFS.Scientific reports · 2026Article
- WiraChain: a blockchain and FHIR-based platform for improving clinical data interoperability in healthcare.Frontiers in public health · 2026Article
- A Systematic Literature Review for Blockchain-Based Healthcare Implementations.Healthcare (Basel, Switzerland) · 2025Review
- A Secure Medical Data Framework Integrating Blockchain and Edge Computing: An Attribute-Based Signcryption Approach.Sensors (Basel, Switzerland) · 2025Article
- Fintech and healthtech synergism: Pioneering a digital healthcare revolution for accessible, affordable, and effective patient-centered care.Journal of family medicine and primary care · 2025Review
- Review
- Privacy preservation in blockchain-based healthcare data sharing: A systematic review.Peer-to-peer networking and applications · 2025Review
- Review
- Treating chronic atrophic gastritis: identifying sub-population based on real-world TCM electronic medical records.Frontiers in pharmacology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
With the rapid development of modern medical technology and the dramatic increase in the amount of medical data, traditional centralized medical information management is facing many challenges. In recent years blockchain, which is a peer-to-peer distributed database, has been increasingly accepted and adopted by different industries and use cases. Key areas of healthcare blockchain applications include electronic medical record (EMR) management, medical device supply chain management, remote condition monitoring, insurance claims and personal health data (PHD) management, among others. Even so, there are a number of challenges in applying blockchain concepts to healthcare and its data, including interoperability, data security privacy, scalability, TPS and so on. While these challenges may hinder the development of blockchain in healthcare scenarios, they can be improved with existing technologies In this paper, we propose a blockchain-based healthcare operations management framework that is combined with the Interplanetary File System (IPFS) for managing EMRs, protects data privacy through a distributed approach while ensuring that this medical ledger is tamper-proof. Doctors act as full nodes, patients can participate in network maintenance either as light nodes or as full nodes, and the hospital acts as the endpoint database of data, i.e., the IPFS node, which saves the arithmetic power of nodes and allows the data stored in the hospitals and departments to be shared with the other organizations that have uploaded the data. Therefore, the integration of blockchain and zero-knowledge proof proposed in this paper helps to protect data privacy and is efficient, better scalable, and more throughput.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.