Evidence map›Paper›PMID 39796933›Full record

ArticleSensors (Basel, Switzerland)2024

AllianceBlockchain in the Governance Innovation of Internet Hospitals.

Xiaofeng Wang, Xiaoguang Yue, Ahthasham Sajid, Noshina Tariq

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. 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.

Xiaofeng WangCollege of Management, Shenzhen University, Shenzhen 518060, China.ORCID 0000-0001-6259-7971
Xiaoguang YueCollege of Management, Shenzhen University, Shenzhen 518060, China.ORCID 0009-0008-9494-5086
Ahthasham SajidMultimedia University, Cyberjaya 63100, Malaysia.ORCID 0000-0002-2829-0893
Noshina TariqDepartment of Artificial Intelligence and Data Science, National University of Computer and Emerging Sciences, Islamabad 44000, Pakistan.ORCID 0000-0002-9754-253X

Funding

National Social Science Foundation of China 20BGL218
6 · The paper itself

Abstract

The rise of Internet hospitals has significant issues associated with data security and governance in managing sensitive patient data. This paper discusses an alliance blockchain (i.e., a private blockchain) model for governance innovation in internet hospitals with an improved encryption methodology. We compare our proposed model, improved Rivest-Shamir-Adleman (RSA) encryption, integrated into the blockchain framework. Improved RSA achieves impressive improvements in all key metrics by increasing the throughput by 24.7% and lowering the latency by 19.8% compared to the base model. Thus, the improved model is more optimized for processing transactions related to healthcare data. Memory usage was also reduced by 14.3%. While encryption time remained pretty close, the decryption time remarkably improved by 97.5%. IoT sensors are one of the foundations for Internet hospitals that produce consistent patient data streams, such as physiological and environmental metrics. The proposed alliance blockchain model enables the secure and efficient real-time management of this sensor data. These results demonstrate the capability of alliance blockchain and cryptographic upgrades in creating safe and efficient governance frameworks for Internet hospitals.

Indexed as

BlockchainComputer SecurityHospitalsInternetAlgorithmsHumansblockchaindistributed role-based access controlelectronic health recordsInternet hospitalsRivest–Shamir–Adleman (RSA)security

Identifiers

PMID39796933
PMCPMC11723095

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.