ArticlePloS one2025
Enhancing healthcare consensus mechanism - A reputation integrated variant of PBFT (BR-PBFT).
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Secure healthcare data management using federated learning, blockchain, and explainable artificial intelligence: a systematic review.Frontiers in digital health · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the rapidly evolving healthcare landscape, adopting blockchain technology requires an optimal consensus mechanism to ensure security, efficiency, reliability, and scalability. This paper examines various consensus methods, including PoW (Proof of Work), PBFT(Practical Byzantine Fault Tolerance), its variants, and node reputation management techniques such as the Beta Reputation Model and EigenTrust score, to determine the most suitable approach for healthcare applications. Among the analyzed algorithms, SBFT (Scalable Byzantine Fault Tolerance) emerges as a strong contender due to its fault tolerance and effectiveness in large-scale environments. Building on these insights, we introduce a light weight consensus BR-PBFT(Beta Reputation integreted PBFT), a novel PBFT variant that integrates a beta reputation scoring system and Verifiable random functions (VRF) for more reliable node selection. This enhancement strengthens trust in the network and mitigates malicious behavior by dynamically adjusting node selection and consensus processes based on reputation metrics. Preliminary evaluations indicate that our PBFT variant built on reputation significantly improves CPU consumption and memory efficiency, offering improved reliability, scalability, and performance. These advancements position BR-PBFT as a promising state-of-the-art solution for secure and efficient blockchain implementations in healthcare.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.