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Record W2794088480 · doi:10.1109/iisa.2017.8316384

A virtual cardiac catheterization laboratory for patient education: The angiogram procedure

2017· article· en· W2794088480 on OpenAlexaff
Kyle Wilcocks, Nour Halabi, Priya Kartick, Álvaro Uribe-Quevedo, Chung‐Wai Chow, Bill Kapralos

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsUniversity of TorontoSt. Michael's HospitalOntario Tech University
Fundersnot available
KeywordsHeadsetCoronary angiogramVirtual patientVirtual realityCardiac catheterizationComputer scienceMedicineRadiologyMedical physicsCoronary angiographyMedical emergencyMultimediaArtificial intelligenceCardiologyNursing

Abstract

fetched live from OpenAlex

A coronary angiogram is a procedure that employs X-ray imaging to view the blood vessels of a patient's heart. Although the procedure is common and routine, it can still be a frightening experience for the patient. Educating the patient about the procedure they will undergo helps reduce this fear while increasing the patient's understanding and awareness, ultimately leading to greater patient outcomes. Here we present a virtual simulation of the angiogram procedure developed specifically for patient education. Using an HTC Vive virtual reality headset, the patient is taken into a virtual catheterization (cath) lab and introduced to the angiogram procedure in a highly immersive, interactive, and engaging virtual environment.

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)0.001
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.003

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 head0.019
GPT teacher head0.308
Teacher spread0.289 · 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
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

Citations8
Published2017
Admission routes1
Has abstractyes

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