Emergency Trauma Radiology: A Rapidly Expanding and Increasingly Important Branch of Diagnostic Imaging
Bibliographic record
Abstract
Medicine, the only profession that labours incessantly to destroy the reason for its existence. James Bryce, First Viscount Bryce British historian and politician (1838-1922) The desire to take medicine is perhaps the greatest feature which distinguishes man from animals. William Osler, First Baronet Osler Canadian physician (1849-1919) Over the past 2-3 decades, emergency radiology has emerged as one of the most rapidly expanding branches within diagnostic radiology. This edition of the CARJ provides a broad perspective of many of the aspects of this important discipline. The growth of emergency radiology has been driven by several factors. One of these factors has been the increased utilisation of the emergency department for the delivery of care. This has been seen in both urban and rural areas where the growing and aging population often does not have timely access to family physicians. Another important aspect has been the increasing ability to intervene therapeutically in many conditions that were previously difficult to treat, such as severe polytrauma injuries, acute pulmonary embolism, myocardial infarction, and stroke. These interventions require a rapid, accurate diagnosis provided by skilled specialists. It, therefore, becomes necessary to have these imaging experts accessible in the emergency department. Furthermore, there has been pressure to protect imaging “turf” because many other specialists, including emergency department physicians, have indicated that, if emergency radiology services are not provided, then they would expect control of, and compensation for, providing these diagnostic services themselves. What has happened in Canada and internationally is that emergency radiology is now being recognized as a distinct subspecialty of radiology. Fellowship training programs and emergency radiology societies are becoming more common. In Canada, we currently have 2 fellowship training programs and more are currently being developed. Along with new innovations in dose reduction and imaging techniques, the role of the emergency radiologist is expanding and the value of this subspecialty is becoming recognized not only within radiology departments but also by emergency department and trauma physicians and Print or Share This Page
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.021 | 0.009 |
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".