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Record W2785800471 · doi:10.1136/gutjnl-2017-315655

Gastrointestinal ultrasound in inflammatory bowel disease: an underused resource with potential paradigm-changing application

2018· review· en· W2785800471 on OpenAlexaff
Robert V. Bryant, Antony B. Friedman, Emily K. Wright, Kirstin M. Taylor, Jakob Begun, Giovanni Maconi, Christian Maaser, Kerri L. Novak, Torsten Kucharzik, Nathan Atkinson, Anil Kumar Asthana

Bibliographic record

VenueGut · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineModalitiesInflammatory bowel diseaseDiseaseIntensive care medicineModality (human–computer interaction)Disease monitoringEndoscopyDisease managementClinical PracticeRadiologyMedical physicsPathologyPhysical therapyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Evolution of treatment targets in IBD has increased the need for objective monitoring of disease activity to guide therapeutic strategy. Although mucosal healing is the current target of therapy in IBD, endoscopy is invasive, expensive and unappealing to patients. GI ultrasound (GIUS) represents a non-invasive modality to assess disease activity in IBD. It is accurate, cost-effective and reproducible. GIUS can be performed at the point of care without specific patient preparation so as to facilitate clinical decision-making. As compared with ileocolonoscopy and other imaging modalities (CT and MRI), GIUS is accurate in diagnosing IBD, detecting complications of disease including fistulae, strictures and abscesses, monitoring disease activity and detecting postoperative disease recurrence. International groups increasingly recognise GIUS as a valuable tool with paradigm-changing application in the management of IBD; however, uptake outside parts of continental Europe has been slow and GIUS is underused in many countries. The aim of this review is to present a pragmatic guide to the positioning of GIUS in IBD clinical practice, providing evidence for use, algorithms for integration into practice, training pathways and a strategic implementation framework.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
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 head0.011
GPT teacher head0.262
Teacher spread0.251 · 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 designNot applicable
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

Citations176
Published2018
Admission routes1
Has abstractyes

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