Thoracic Ultrasound – EFSUMB Training Recommendations – a Position Paper
Bibliographic record
Abstract
A wide range of medical specialists increasingly use thoracic ultrasound and transthoracic ultrasound-guided interventions in their clinical practice. To ensure high quality and standardized practice across specialties, this position paper of the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) describes the training requirements for thoracic ultrasound. The recommendations follow the three EFSUMB competency levels for medical ultrasound practice. Level 1 describes the skills required to perform basic thoracic ultrasound examinations and basic interventions independently, level 2 includes more advanced transthoracic ultrasound imaging and guided interventions, while level 3 involves the practice of high-level thoracic ultrasound and the use of advanced technologies. Previously, a predefined minimum number of ultrasound examinations was used to determine competence, but in recent years, a general shift towards competency-based training and assessment has been implemented. For each EFSUMB level, we outline the theoretical knowledge and practical skills needed for clinical practice.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.027 |
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".