Evidence map›Paper›PMID 40363296›Full record

ArticleSensors (Basel, Switzerland)2025

A Secure Medical Data Framework Integrating Blockchain and Edge Computing: An Attribute-Based Signcryption Approach.

Tengyue Dou, Zhiming Zheng, Wangjie Qiu, Chunxia Ge

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Tengyue DouThe Second School of Clinical Medicine, Binzhou Medical University, Yantai 264003, China.
Zhiming ZhengHealth Blockchain Research Center, Binzhou Medical University, Yantai 264003, China.
Wangjie QiuHealth Blockchain Research Center, Binzhou Medical University, Yantai 264003, China.
Chunxia GeInstitute of Medical Artificial Intelligence, Binzhou Medical University, Yantai 264003, China.

Funding

Science and Technology project of traditional Chinese medicine in Shandong province M-2023152
6 · The paper itself

Abstract

With the rapid digitization of healthcare information, ensuring the security and privacy of patient data has become a critical research focus. This study introduces a novel Attribute-Based Signcryption (ABSC) framework combining blockchain and edge computing technologies to efficiently and securely manage medical data. The framework collects data via smart devices, which is then processed and encrypted at edge nodes and stored securely on the blockchain. Access to sensitive information is controlled with precision by predefined attribute sets, ensuring that only authorized users can retrieve the data. The experimental results demonstrate the significant advantages of this framework in improving data security, reducing computational overhead, and enhancing access efficiency.

Indexed as

access controlattribute-based signcryptionblockchainedge computingmedical data security

Identifiers

PMID40363296
PMCPMC12074239

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.