Evidence map›Paper›PMID 39877624›Full record

ArticleHeliyon2025

Efficient information exchange approach for medical IoT based on AI and DAG-enabled blockchain.

Shanqin Wang, Gangxin Du, Shufan Dai, Mengjun Miao, Miao Zhang

Abstract read
In one paragraph

Article in Heliyon, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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

5 authors.

Shanqin WangSchool of Information Engineering, Chuzhou Polytechnic, Chuzhou, 239000, Anhui, China.
Gangxin DuSany Energy Equipment Co., Ltd, Zhuzhou, 412000, Hunan, China.
Shufan DaiSchool of Information Engineering, Chuzhou Polytechnic, Chuzhou, 239000, Anhui, China.
Mengjun MiaoSchool of Information Engineering, Chuzhou Polytechnic, Chuzhou, 239000, Anhui, China.
Miao ZhangSchool of Information Engineering, Chuzhou Polytechnic, Chuzhou, 239000, Anhui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of artificial intelligence (AI) based medical Internet of Things (IoT) technology plays a crucial role in making the collection and exchange of medical information more convenient. However, security, privacy, and efficiency issues during information exchange have become pressing challenges. While many scholars have proposed solutions based on AI and blockchain to address these issues, few have focused on the impact of the slow consensus algorithm of blockchain on the efficiency of information exchange. To improve the efficiency of information exchange, we propose an information exchange approach based on AI and DAG-enabled blockchain, providing a secure and efficient environment for information exchange in the medical IoT. Additionally, to enhance the efficiency of information exchange in the medical IoT, a novel tip selection algorithm is introduced to reduce the time delay in reaching consensus, thereby enabling faster acquisition of trusted information via blockchain. Simulation results demonstrate that compared to methods based on traditional DAG-enabled blockchain, the approach proposed in this paper improves the efficiency of information exchange.

Indexed as

AIDAG-Enabled blockchainInformation exchangeMedical IoT

Identifiers

PMID39877624
PMCPMC11773007

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.