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Record W2051705016 · doi:10.1121/1.4779612

High intensity focused ultrasound for treatment of bleeding and air leaks due to lung trauma

2002· article· en· W2051705016 on OpenAlexaff
Shahram Vaezy, Roy W. Martin, Larry A. Crum, Carol Cornejo, Jerry Jurkovich, Sam R. Sharar, Savvas Nicolaou

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2002
Typearticle
Languageen
FieldMedicine
TopicThyroid and Parathyroid Surgery
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHigh-intensity focused ultrasoundHemostasisTransducerMedicineUltrasoundIntensity (physics)Biomedical engineeringSurgeryMaterials scienceRadiologyAcousticsOptics

Abstract

fetched live from OpenAlex

In thoracic surgery, bleeding and air leaks from the lungs can be difficult to control. We have investigated the use of high intensity focused ultrasound (HIFU) for control of lung bleeding and air leaks in operative situations. An intraoperative HIFU device, equipped with a Titanium coupler, was used. The HIFU transducer was a PZT-8 concave element, with a focal length of 5 cm, and a diameter of 2.5 cm. The transducer was operated at 5.7 MHz and intensity of 5000 W/cm2. The coupler length was 4 cm, placing the focal volume, defined by full-width half-maximum at approximately 1 cm from the tip of the coupler. A pig animal model was used. Incisions in the lung were made, having lengths of 2–5 cm, and depths of 3–10 mm which created both parenchymal hemorrhage and air leakage from the lung. HIFU was applied within 10 seconds of inducing the injury. The average hemostasis time was approximately 60 seconds. All incisions were completely sealed, and no blood or air leaked from the incisions. Intraoperative HIFU may provide an effective method in various pulmonary surgery indications, and hemostasis and control of air leaks from lacerations due to trauma. [Work supported by NIH and NSF.]

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.282

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.023
GPT teacher head0.260
Teacher spread0.237 · 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 designBench or experimental
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

Citations0
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicThyroid and Parathyroid SurgeryFrench-language works237,207