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Record W4407736619 · doi:10.1109/mitp.2025.3529858

The Blockchain for Personalized Medicine

2025· article· en· W4407736619 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

VenueIT Professional · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsBlockchainComputer sciencePersonalized medicineComputer securityBioinformatics

Abstract

fetched live from OpenAlex

The advent of personalized medicine, or precision medicine, promises a revolution in healthcare, offering treatments tailor-made to the genetic makeup and lifestyle choices of individuals. Despite the significant potential, its integration into mainstream healthcare is hindered by several challenges, including data silos, privacy concerns, and a lack of coordinated efforts across the healthcare ecosystem. This paper examines the role of Blockchain technology as a solution to these obstacles. By leveraging the unique attributes of Blockchain we propose a model for a healthcare system that aligns with the ideals of personalized medicine. Through conceptual analysis and discussing initiatives like the 100,000 Genomes Project, we illustrate the synergy between Blockchain and personalized medicine. The paper concludes by envisioning an integrated healthcare delivery model that not only advances drug research and treatments but also significantly improves patient outcomes through personalized care approaches.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.465
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.342
Teacher spread0.322 · 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