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Record W2067472081 · doi:10.4018/jhdri.2009040104

Wireless for Managing Health Care

2009· article· en· W2067472081 on OpenAlexaff
Esko Alasaarela, Ravi Nemana, Steven DeMello, Nick Oliver, Masako Miyazaki

Bibliographic record

VenueInternational Journal of Healthcare Delivery Reform Initiatives · 2009
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHealth careKey (lock)Process (computing)WirelessComputer scienceQuality (philosophy)Process managementKnowledge managementBusinessComputer securityTelecommunications

Abstract

fetched live from OpenAlex

The Wirhe project is an international collaborative study that focused on the future of healthcare needs, technology requirements and solutions for effective use of wireless technologies for health care delivery. This paper presents results of a Wirhe survey of 85 experts and individual interviews with 35 experts. Key findings include: 1) both notable quality improvements and process enhancements can be expected from effectively utilizing wireless technologies and mobile solutions, 2) integration of personal health monitoring and professional health management is a key issue to be addressed and 3) health promotion and illness prevention efforts can grow by utilizing mobile solutions. We propose a framework that can be used in developing wireless health care solutions for managing diseases and related health problems. This framework can also be used to structure and stratify the needs of technologies and solutions, and to estimate their market potential.

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)0.003
metaresearch head score (Gemma)0.007
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: Commentary · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.049
GPT teacher head0.456
Teacher spread0.407 · 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
GenreCommentary

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

Citations5
Published2009
Admission routes1
Has abstractyes

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