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Record W1539475402 · doi:10.5772/24023

Endorectal Ultrasound Scan

2011· book-chapter· en· W1539475402 on OpenAlexaff
Rani Kanthan, Selliah Kanth

Bibliographic record

VenueInTech eBooks · 2011
Typebook-chapter
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsRoyal University Hospital
Fundersnot available
KeywordsRectumMedicineRadiologyUltrasoundEndoscopic ultrasoundSedationAnusImage qualitySurgeryComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

1.1 Endoscopic ultrasound anatomy of rectum Assessment of the rectum with endoscopic ultrasound [EUS] has evolved as an excellent tool in the management of malignant as well as benign diseases of the rectum and anus. The endoluminal ultrasound provides accurate evaluation of rectal, perirectal and perianal pathology. Initially, the standard radial endoscopic ultrasound scan was used in the assessment of the rectum as people were familiar with its usage in the management of upper gastrointestinal tract problems. The rigid endoscopic ultrasound scan has been used since the early 80’s. Improvements in the instrument as well as high resolution of the ultrasonic waves have resulted in very significantly improved image quality and accurate interpretation of this particular examination. Color Doppler as well as 3D imaging has also added some benefits to this modality. The EUS has now become an excellent tool in the preoperative staging of low rectal cancer compared to CT scan and/or MRI. The rigid probe is 20cm in length, has the rotating transducer at the tip covered by a balloon filled with water. There are different types of linear as well as radial scanning devices available in the market and the frequencies vary from 3.5 MHz to 15MHz. EUS is portable, cost effective and can be completed in a short time with minimal discomfort to the patient. Most of the patients can have it done without any sedation and the recovery time is very short.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.829
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.037
GPT teacher head0.269
Teacher spread0.232 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2011
Admission routes1
Has abstractyes

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