Radiologist income, receipts, and academic performance: an analysis of many nations
Bibliographic record
Abstract
Background Considerable interest exists in comparison between healthcare systems across multiple countries, especially where cost enters the discussion. Purpose To evaluate the relationship between radiologists' income, receipts for studies, and academic performance across multiple countries. Material and Methods The annual income of radiologists and receipts for computed tomography (CT) and magnetic resonance imaging (MRI) were obtained based on a survey sent to expert radiologists practicing in 23 countries of varying developmental status. Articles published in generalist radiology journals determined the academic performance of each country. Results Among the developed countries, Canada has the highest estimated annual income for both private ($700,000/year) and university radiologists ($600,000/year) while Spain has the lowest income for private practice ($68,000/year) and Portugal has the lowest income for university practice ($57,300/year). Among the developing countries, Saudi Arabia has the highest incomes for both private ($210,000/year) and university ($140,000/year) radiologists and Vietnam has the lowest incomes for both private ($30,000/year) and university ($6,000/year) radiologists. Total receipts for CT and MRI studies ranged from $80/study (Portugal) to $1000/study (USA) in developed countries, and ranged from $30/study (Egypt) to $700/study (Saudi Arabia) in developing countries. A moderate correlation ( r = 0.482) was seen between radiologist's income and the receipts for combined practice in all countries. The radiology journal academic quotient was highest in The Netherlands among developed countries, and Turkey among developing countries. Conclusion A relatively broad range of radiologists' income is observed among developed and developing countries, which shows correlation with the receipts for advanced imaging studies. Countries with an acceptable compromise between income, receipts, and academic performance, may be the best models for other countries to emulate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".