An Internist's Approach to Radiologic Examination of the Liver
Bibliographic record
Abstract
Imaging is essential when evaluating suspected hepatobiliary disease. Ultrasound is the most widely available cross-sectional imaging modality. It is portable, inexpensive, and does not use ionizing radiation. Generally, the liver offers an excellent acoustic window, facilitating ultrasound evaluation for both diffuse and focal hepatic disease. It also evaluates the gallbladder and bile ducts in detail. Doppler ultrasound assesses patency of the hepatic vasculature and documents the direction and character of blood flow. Consequently, ultrasound is the first choice when imaging the majority of patients with suspected hepatobiliary disease. It will frequently answer the clinical question alone or will direct the next most appropriate imaging investigation. Computed tomography, magnetic resonance, endoscopic retrograde cholangiopancreatography, endoscopic ultrasound, and image-guided biopsy may be necessary beyond ultrasound, either alone or in combination, for certain diagnoses. This chapter outlines imaging algorithms for common hepatobiliary scenarios that present to the general internist.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.036 | 0.015 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".