Evidence map›Paper›PMID 29956058›Full record

ArticleJournal of medical systems2018

Blockchain-Based Data Preservation System for Medical Data.

Hongyu Li, Liehuang Zhu, Meng Shen, Feng Gao, Xiaoling Tao, Sheng Liu

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of medical systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  18. A Comprehensive Survey on Security and Privacy for Electronic Health Data.International journal of environmental research and public health · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Hongyu LiBeijing Institute of Technology, Beijing, China.
Liehuang ZhuBeijing Institute of Technology, Beijing, China.
Meng ShenBeijing Institute of Technology, Beijing, China. shenmeng@bit.edu.cn.
Feng GaoBeijing Institute of Technology, Beijing, China.
Xiaoling TaoGuilin University of Electronic Technology, Guilin, China.
Sheng LiuUnion Mobile Finacial Technology Co., Ltd., Beijing, China.

Funding

Guangxi Cooperative Innovation Center of cloud computing and Big Data No.YD16E14National Science Foundation of China under Grant 61602039
6 · The paper itself

Abstract

Medical care has become an indispensable part of people's lives, with a dramatic increase in the volume of medical data (e.g., diagnosis certificates and medical records). Medical data, however, is easily stolen, tampered with, or even completely deleted. If the above occurs, medical data cannot be recorded or retrieved in a reliable manner, resulting in delay treatment progress, even endanger the patient's life. In this paper, we propose a novel blockchain-based data preservation system (DPS) for medical data. To provide a reliable storage solution to ensure the primitiveness and verifiability of stored data while preserving privacy for users, we leverage the blockchain framework. With the proposed DPS, users can preserve important data in perpetuity, and the originality of the data can be verified if tampering is suspected. In addition, we use prudent data storage strategies and a variety of cryptographic algorithms to guarantee user privacy; e.g., an adversary is unable to read the plain text even if the data are stolen. We implement a prototype of the DPS based on the real world blockchain-based platform Ethereum. Performance evaluation results demonstrate the effectiveness and efficiency of the proposed system.

Indexed as

AlgorithmsComputer SecurityElectronic Health RecordsHumansPrivacyBlockchainData preservationEthereumMedical dataSensitive data

Identifiers

PMID29956058

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.