Evidence map›Paper›PMID 36991986›Full record

ReviewSensors (Basel, Switzerland)2023

The Potential of Blockchain Technology in Dental Healthcare: A Literature Review.

Takua Mokhamed, Manar Abu Talib, Mohammad Adel Moufti, Sohail Abbas, Faheem Khan

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2023. 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. Review
  2. Review
  3. Review
  4. Article
  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

5 authors.

Takua MokhamedDepartment of Computer Science, College of Computing and Informatics, University of Sharjah, Sharjah 27272, United Arab Emirates.
Manar Abu TalibDepartment of Computer Science, College of Computing and Informatics, University of Sharjah, Sharjah 27272, United Arab Emirates.
Mohammad Adel MouftiDepartment of Preventive and Restorative Dentistry, College of Dental Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates.
Sohail AbbasDepartment of Computer Science, College of Computing and Informatics, University of Sharjah, Sharjah 27272, United Arab Emirates.ORCID 0000-0002-2287-3801
Faheem KhanArtificial Intelligence Lab, Department of Computer Engineering, Gachon University, Seongnam 13557, Republic of Korea.ORCID 0000-0001-6220-0225

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Blockchain technology in the healthcare industry has potential to enable enhanced privacy, increased security, and an interoperable data record. Blockchain technology is being implemented in dental care systems to store and share medical information, improve insurance claims, and provide innovative dental data ledgers. Because the healthcare sector is a large and ever-growing industry, the use of blockchain technology would have many benefits. To improve dental care delivery, researchers advocate using blockchain technology and smart contracts due to their numerous advantages. In this research, we concentrate on blockchain-based dental care systems. In particular, we examine the current research literature, pinpoint issues with existing dental care systems, and consider how blockchain technology may be used to address these issues. Finally, the limitations of the proposed blockchain-based dental care systems are discussed which may be regarded as open issues.

Indexed as

BlockchainComputer SecurityDelivery of Health CarePrivacyTechnologyblockchaindentistryelectronic dental recordssmart contract

Identifiers

PMID36991986
PMCPMC10052552

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.