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Record W2163285407 · doi:10.1109/iembs.2009.5333884

Service oriented architecture for the integration of clinical and physiological data for real-time event stream processing

2009· article· en· W2163285407 on OpenAlex
Rishikesan Kamaleswaran, Carolyn McGregor, Jennifer Percival

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicHealthcare Technology and Patient Monitoring
Canadian institutionsOntario Tech University
FundersCanada Research Chairs
KeywordsStandardizationComputer scienceComplex event processingArchitectureEvent (particle physics)Service-oriented architectureData integrationService (business)Real-time computingSoftware engineeringDatabaseWeb serviceWorld Wide WebOperating system

Abstract

fetched live from OpenAlex

This paper proposes a framework for the integration of physiological and clinical health data within a Service-Oriented architecture framework. This integration will subsequently be used in real-time event stream processing in intelligent patient monitoring devices. Service-oriented architecture offers a unique method of integrating health data as information is collected from multiple medical devices that lack any substantial means of standardization. Employing various services to facilitate the transmission and integration of these data will result in significant improvement in both efficacy and analytical velocity of intelligent patient monitoring systems. We demonstrate this approach within the Neonatal Intensive Care setting.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.987
Threshold uncertainty score0.145

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 science0.0000.000
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 head0.189
GPT teacher head0.463
Teacher spread0.274 · 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