Evidence map›Paper›PMID 36501776›Full record

ArticleSensors (Basel, Switzerland)2022

A Machine-Learning-Blockchain-Based Authentication Using Smart Contracts for an IoHT System.

Rajkumar Gaur, Shiva Prakash, Sanjay Kumar, Kumar Abhishek, Mounira Msahli, Abdul Wahid

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Enhancing Cancer Care through Blockchain Technology.Asian Pacific journal of cancer prevention : APJCP · 2025
    Review
  5. 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

6 authors.

Rajkumar GaurITCA, Madan Mohan Malaviya University of Technology Gorakhpur, Gorakhpur 273016, India.ORCID 0000-0003-2792-6535
Shiva PrakashITCA, Madan Mohan Malaviya University of Technology Gorakhpur, Gorakhpur 273016, India.
Sanjay KumarITD, Rajkiya Engineering College Azamgarh, Deogaon 276201, India.ORCID 0000-0002-0922-6474
Kumar AbhishekCSED, National Institute of Technology Patna, Patna 800005, India.ORCID 0000-0001-6825-2392
Mounira MsahliTelecom Paris, Institut Polytechnique de Paris, 91120 Palaiseau, France.
Abdul WahidTelecom Paris, Institut Polytechnique de Paris, 91120 Palaiseau, France.ORCID 0000-0003-2835-6853

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nowadays, finding genetic components and determining the likelihood that treatment would be helpful for patients are the key issues in the medical field. Medical data storage in a centralized system is complex. Data storage, on the other hand, has recently been distributed electronically in a cloud-based system, allowing access to the data at any time through a cloud server or blockchain-based ledger system. The blockchain is essential to managing safe and decentralized transactions in cryptography systems such as bitcoin and Ethereum. The blockchain stores information in different blocks, each of which has a set capacity. Data processing and storage are more effective and better for data management when blockchain and machine learning are integrated. Therefore, we have proposed a machine-learning-blockchain-based smart-contract system that improves security, reduces consumption, and can be trusted for real-time medical applications. The accuracy and computation performance of the IoHT system are safely improved by our system.

Indexed as

BlockchainData ManagementHumansMachine LearningProbabilityTrustblockchainCP-ABEIoHTML-basedsecure systemsmart contractSVMtraining set

Identifiers

PMID36501776
PMCPMC9741337

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.