Bibliographic record
Abstract
Radiologic evaluation of neonatal bowel obstruction is challenging owing to the overlapping clinical features and imaging appearances of the most common differential diagnoses. The key to providing an appropriate differential diagnosis comes from a combination of the patient's gestational age, clinical features, and imaging findings. While assessment of radiographs can confirm bowel obstruction and indicate whether it is likely proximal or distal, additional findings at upper or lower gastrointestinal contrast study together with use of US are important in providing an appropriate differential diagnosis. The authors provide an in-depth assessment of the appearances of the most common differential diagnoses of proximal and distal neonatal bowel obstruction at abdominal radiography and upper and lower gastrointestinal contrast studies. These are divided into imaging patterns and their associated differential diagnoses on the basis of abdominal radiographic findings. These findings include esophageal atresia variants including the “single bubble,” “double bubble,” and “triple bubble” and distal bowel obstruction involving the small and large bowel. Entities discussed include esophageal atresia, hypertrophic pyloric stenosis, pyloric atresia, duodenal atresia, duodenal web, malrotation with midgut volvulus, jejunal atresia, ileal atresia, meconium ileus, segmental volvulus, internal hernia, colonic atresia, Hirschsprung disease, and functional immaturity of the large bowel. The authors include the advantages of abdominal US in this algorithm, particularly for hypertrophic pyloric stenosis, duodenal web, malrotation with midgut volvulus, and segmental volvulus. ©RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center. An earlier incorrect version of this article appeared online. This article was corrected on July 27, 2023.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".