MétaCan
Menu
Back to cohort
Record W4388098718 · doi:10.3390/sci5040041

Privacy and Security of Blockchain in Healthcare: Applications, Challenges, and Future Perspectives

2023· article· en· W4388098718 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSci · 2023
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsUniversity Canada West
Fundersnot available
KeywordsBlockchainHealth careComputer securityInformation privacyComputer scienceState (computer science)Internet privacyBusinessPolitical scienceLaw

Abstract

fetched live from OpenAlex

Blockchain offers a cutting-edge solution for storing medical data, carrying out medical transactions, and establishing trust for medical data integration and exchange in a decentralized open healthcare network setting. While blockchain in healthcare has garnered considerable attention, privacy and security concerns remain at the center of the debate when adopting blockchain for information exchange in healthcare. This paper presents research on the subject of blockchain’s privacy and security in healthcare from 2017 to 2022. In light of the existing literature, this critical evaluation assesses the current state of affairs, with a particular emphasis on papers that deal with practical applications and difficulties. By providing a critical evaluation, this review provides insight into prospective future study directions and advances.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.339
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.260
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it