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Record W4393193968 · doi:10.1016/j.jscai.2023.101289

Validation Study of Two Artificial Intelligence–Based Preplanning Methods for Transcatheter Aortic Valve Replacement Procedures

2024· article· en· W4393193968 on OpenAlexafffund
Denis Corbin, Marcel Santaló-Corcoy, Olivier Tastet, Patrícia de Medeiros Loureiro Lopes, Janelle Schrot, Thomas Modine, Anita Asgar, Frédéric Lesage, Walid Ben Ali

Bibliographic record

VenueJournal of the Society for Cardiovascular Angiography & Interventions · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsPolytechnique MontréalMontreal Heart Institute
FundersFonds de Recherche du Québec - Santé
KeywordsValve replacementAortic valve replacementMedicineStenosisAortic valve stenosisAortic valveCardiologyRadiologyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Transcatheter aortic valve replacement (TAVR) is a critical procedure for patients with aortic stenosis, requiring precise preoperative planning for optimal outcomes. These measurements can be time-consuming to obtain and may be subject to substantial interindividual variability, especially for inexperienced cardiologists. Two unique and fully automatic artificial intelligence (AI)-based planning methods were used to assess the validity of AI to quantify anatomical characteristics necessary for TAVR patient evaluation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.818
Threshold uncertainty score0.560

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.446
Bibliometrics0.0000.001
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 head0.056
GPT teacher head0.435
Teacher spread0.378 · 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.

Study designMeta-analysis
Domainnot available
GenreEmpirical

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

Citations4
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the Society for Cardiovascular Angiography & InterventionsSame topicCardiac Valve Diseases and TreatmentsFrench-language works237,207