Evidence map›Paper›PMID 33411842›Full record

ArticlePloS one2021

A data-sharing scheme that supports multi-keyword search for electronic medical records.

Shufen Niu, Wenke Liu, Song Han, Lizhi Fang

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Shufen NiuCollege of Computer Science and Engineering, Northwest Normal University, Lanzhou, Gansu, China.
Wenke LiuCollege of Computer Science and Engineering, Northwest Normal University, Lanzhou, Gansu, China.ORCID 0000-0001-7923-1992
Song HanCollege of Computer Science and Engineering, Northwest Normal University, Lanzhou, Gansu, China.
Lizhi FangCollege of Computer Science and Engineering, Northwest Normal University, Lanzhou, Gansu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As cloud storage technology develops, data sharing of cloud-based electronic medical records (EMRs) has become a hot topic in the academia and healthcare sectors. To solve the problem of secure search and sharing of EMR in cloud platforms, an EMR data-sharing scheme supporting multi-keyword search is proposed. The proposed scheme combines searchable encryption and proxy re-encryption technologies to perform keyword search and achieve secure sharing of encrypted EMR. At the same time, the scheme uses a traceable pseudo identity to protect the patient's private information. Our scheme is proven secure based on the modified Bilinear Diffie-Hellman assumption and Quotient Decisional Bilinear Diffie-Hellman assumption under the random oracle model. The performance of our scheme is evaluated through theoretical analysis and numerical simulation.

Indexed as

Electronic Health RecordsInformation DisseminationInformation Storage and RetrievalCloud ComputingComputer SecurityHumansSearch Engine

Identifiers

PMID33411842
PMCPMC7790426

What OpenQuestion holds

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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.