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Record W2965500900 · doi:10.1109/seh.2019.00011

Blockchain: A Panacea for Electronic Health Records?

2019· article· en· W2965500900 on OpenAlex
Mohamad Kassab, Joanna F. DeFranco, Tarek Malas, Valdemar Vicente Graciano Neto, Giuseppe Destefanis

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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsBlockchainHealth recordsPanacea (medicine)Health careElectronic health recordComputer scienceComputer securityInternet privacyHealth dataHealthcare systemBusinessKnowledge managementMedicine

Abstract

fetched live from OpenAlex

Healthcare systems have been supported by technology to help improve the user experience with the entire health system. However, many operational challenges still remain, in particular those related to a unified management of electronic health records (EHR) that could enable multiple doctors to have access to the complete health history of their patient. Blockchain could support unified records, data security and privacy improvement and insurance decisions/transactions making it an effective solution for the above mentioned healthcare technology challenges. The main contribution of this paper is providing preliminary results of a literature review on the adoption of blockchain to support the management of EHR in health systems - along with the benefits and challenges.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score0.320

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 head0.009
GPT teacher head0.249
Teacher spread0.240 · 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