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Record W3201813997 · doi:10.1109/iotm.0101.2000182

A Multistage Blockchain-Based Secure and Trustworthy Smart Healthcare System Using ECG Characteristic

2021· article· en· W3201813997 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

VenueIEEE Internet of Things Magazine · 2021
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsMcGill University
FundersNational Natural Science Foundation of China
KeywordsComputer scienceEncryptionComputer securityBlockchainSecure transmissionComputer network

Abstract

fetched live from OpenAlex

With the rapid development of advanced biomedical sensors, the Internet of Things, and modern wireless communication technologies, smart healthcare systems provide feasible solutions to the problems of population aging and telemedicine services. However, physiological information involves personal privacy, and the data security concern during the transmission of information on public channels has become a critical issue that has restricted the wider acceptance of smart healthcare systems. In this article, a secure and trustworthy smart healthcare system interoperating with wireless body area networks based on multistage blockchain is proposed. The security scheme provides a completely secure and trustworthy environment covering the entire data flow from the front-end to the back-end. The evaluation results show that the encryption scheme based on piecewise linear chaotic map can resist common attack methods and reduce encryption time. The system has the advantages of low complexity for encryption scheme, and larger capacity and efficiency for the blockchain-based data transmission and storage system.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.975
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.241
Teacher spread0.228 · 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