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Record W4286785473 · doi:10.33448/rsd-v11i9.31721

Development of a customized three-dimensional airway model

2022· article· en· W4286785473 on OpenAlex
Mateus Samuel Tonetto, Hugo Goulart de Oliveira, André Frotta Müller, Paulo Roberto Stefani Sanches, Luciano Folador, Felipe Soares Torres, Tiago Severo Garcia

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResearch Society and Development · 2022
Typearticle
Languageen
FieldMedicine
TopicRadiomics and Machine Learning in Medical Imaging
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsIntraclass correlationConfidence intervalComputed tomographyNuclear medicineAirwayReplicateSoftware3d modelBiomedical engineeringComputer scienceArtificial intelligenceMedicineMathematicsRadiologyStatisticsSurgery

Abstract

fetched live from OpenAlex

This study aimed to develop a customized, three-dimensional airway model based on relevant medical images, using additive manufacturing techniques. We evaluated the model’s ability to replicate the dimensions of the images acquired from the chest of a patient using multi-detector computed tomography (CT). Using dedicated software, a three-dimensional mesh was created based on the images. A multi-detector CT study of the full-scale printed three-dimensional airways model was subsequently carried out to compare its dimensions with that of the original study at four predetermined points. The observed median differences at the four points were 0.4 mm (p = 0.686), -1.3 mm (p = 0.138), 0.7 mm (p = 0.141), and 0.1 mm (p = 0.892). The intraclass correlation coefficient between the measurements made on the patient and those on the model was 0.98 (95% confidence interval: 0.96–0.99, p < 0.001). We successfully developed a three-dimensional model of the airway based on its corresponding medical images. The differences in the dimensions between the model and the original images were in line with those observed in previous studies and are presumably irrelevant for most applications.

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.

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)0.003
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.703
Threshold uncertainty score0.691

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.064
GPT teacher head0.366
Teacher spread0.301 · 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