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Record W2119707622 · doi:10.1109/hicss.2002.994069

Using the XML-based Clinical Document Architecture for exchange of structured discharge summaries

2003· article· en· W2119707622 on OpenAlexaff
Grace I. Paterson, Michael Shepherd, Xiaoli Wang, Carolyn Watters, David Zitner

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiomedical Text Mining and Ontologies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsXMLComputer scienceArchitectureHealth careMarkup languageWorld Wide WebMedicine

Abstract

fetched live from OpenAlex

The XML-based Clinical Document Architecture (CDA) for document exchange defines a three-level document architecture with each higher level adding more specificity to the markup of the document. Such a layered architecture also meets the requirement for semantic processing of hierarchically structured clinical documents. The CDA supports shared care between hospital-based and community-based physicians, knowledge integration by permitting external links to other documents, and outcomes research through the capture of discrete and coded clinical data. The research reported has led to the successful prototyping of a CDA-based Structured Discharge Summary system. Structured discharge summaries are used to move clinical information from the clinical environment, such as the geriatrics department of a hospital, to the community environment of family practice. They are an education, communication, research, and administration tool in the Departments of Medicine and Family Medicine and at the Queen Elizabeth II Health Sciences Centre.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.019
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0020.002
Scholarly communication0.0100.008
Open science0.0030.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.005

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 head0.056
GPT teacher head0.365
Teacher spread0.309 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations31
Published2003
Admission routes1
Has abstractyes

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