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Record W2005516096 · doi:10.4103/1319-3767.153812

Nonalcoholic fatty liver disease: Noninvasive methods of diagnosing hepatic steatosis

2015· review· en· W2005516096 on OpenAlexaff
Mazen Hassanain, Rasha Alshaalan, Murad Aljiffry, Said A. Al‐Busafi, Peter Metrakos

Bibliographic record

VenueSaudi Journal of Gastroenterology · 2015
Typereview
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsNonalcoholic fatty liver diseaseMedicineSteatosisTransient elastographyLiver biopsyFatty liverPopulationRadiologyInternal medicineGold standard (test)GastroenterologyLiver diseasePathologyBiopsyDisease

Abstract

fetched live from OpenAlex

Hepatic steatosis is the buildup of lipids within hepatocytes. It is the simplest stage in nonalcoholic fatty liver disease (NAFLD). It occurs in approximately 30% of the general population and as much as 90% of the obese population in the United States. It may progress to nonalcoholic steatohepatitis, which is a state of hepatocellular inflammation and damage in response to the accumulated fat. Liver biopsy remains the gold standard tool to diagnose and stage NAFLD. However, it comes with the risk of complications ranging from simple pain to life-threatening bleeding. It is also associated with sampling error. For these reasons, a variety of noninvasive radiological markers, including ultrasound, computed tomography, magnetic resonance spectroscopy, and the controlled attenuation parameter using transient elastography and Xenon-133 scan have been proposed to increase our ability to diagnose NAFLD, hence avoiding liver biopsy. The aim of this review is to discuss the utility and accuracy of using available noninvasive diagnostic modalities for fatty liver in NAFLD.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.776
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.078
GPT teacher head0.398
Teacher spread0.320 · 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 designOther design
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

Citations41
Published2015
Admission routes1
Has abstractyes

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