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Record W7132987834

Magnetic Resonance Imaging Schedule Optimization at JDMI

2022· dissertation· W7132987834 on OpenAlexaboutno aff
Dylan Patrick Eusebe Camus

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldHealth Professions
TopicHealthcare Operations and Scheduling Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsMagnetic resonance imagingMedical imagingScheduling (production processes)ScheduleMri scanFlexibility (engineering)
DOInot available

Abstract

fetched live from OpenAlex

The Joint Department of Medical Imaging (JDMI) is the largest academic medical imaging department in Canada. Long Magnetic Resonance Imaging (MRI) wait times for lower priority patients remain a critical issue at JDMI. There is, however, also a particular focus given to the wait time equity and MRI access discrepancies between patient sub-populations. An MRI scheduling framework is therefore proposed to: 1) maximize machine utilization through efficient shift scheduling using Branch-and-Price (B&P); and 2) ensure clinical MRI machine capacity remains aligned with incoming ordered scan demand, maximizing patient wait time equity. Schedule flexibility is successfully captured using the proposed B&P shift scheduling model through staff configuration scenarios. Additionally, the number of different scan types performed by MRI technologists across a week is considered during MRI capacity re-alignment. We demonstrate an average 22% improvement in exposure to different scan types per technologist compared to current MRI capacity allocation.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.549
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0090.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.1020.001

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 head0.044
GPT teacher head0.433
Teacher spread0.389 · 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; both teacher heads agree on what is shown here.

Study designSimulation or modeling
Domainnot available
GenreOther

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

Citations0
Published2022
Admission routes1
Has abstractyes

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