MétaCan
Menu
Back to cohort
Record W2520733524 · doi:10.4244/eijv12sya3

Fluoroscopic “heart chamber” anatomy – the case for imaging modality-independent terminology

2016· review· en· W2520733524 on OpenAlexaff
Nicolò Piazza, Darren Mylotte, Pascal Thériault-Lauzier

Bibliographic record

VenueEuroIntervention · 2016
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsRoyal Victoria Hospital
Fundersnot available
KeywordsMedicineModality (human–computer interaction)RadiologyContext (archaeology)ModalitiesPercutaneousMultislice computed tomographyCardiac imagingTerminologyMedical physicsComputed tomographyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Interventional cardiologists have traditionally relied upon fluoro-scopic imaging for percutaneous coronary interventions. Transcatheter structural heart interventions, however, require additional imaging modalities such as echocardiography and multislice computed tomography (MSCT) for pre-, intra- and post-procedural assistance. MSCT has emerged as the critical imaging modality for patient and device selection prior to transcatheter structural heart interventions. MSCT is unique as it provides a complete 3-dimensional (3D) dataset of the heart and vasculature that is amenable to multiplanar reconstruction for 2-dimensional (2D) or volume-rendered interpretations. Herein, we present a modality-independent terminology for understanding volumetric images in the context of transcatheter heart valve therapies. The goal of this system is to allow physicians to readily interpret the orientation of fluoroscopic, MSCT, echocardiographic and MRI images, thus generalising their understanding of cardiac anatomy to all imaging modalities.

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)0.000
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: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score0.836

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.005
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 head0.048
GPT teacher head0.439
Teacher spread0.392 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations14
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueEuroInterventionSame topicCardiac Valve Diseases and TreatmentsFrench-language works237,207