Use of three-dimensional printing for simulation in ultrasound education: a scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: There is a significant learning curve when teaching ultrasonography to medical trainees; task trainers can help learners to bridge this gap and develop their skills. Three-dimensional printing technology has the potential to be a great tool in the development of such simulators. Objective: This scoping review aimed to identify what 3D-printed models have been used in ultrasound education to date, how they were created and the pros and limitations involved. Design: Researchers searched three online databases to identify 3D-printed ultrasound models used in medical education. Results: Twelve suitable publications were identified for inclusion in this review. The models from included articles simulated largely low frequency and/or high stakes events, with many models simulating needle guidance procedures. Most models were created by using patient imaging data and a computer-aided design software to print structures directly or print casting molds. The benefits of 3D-printed educational trainers are their low cost, reproducibility, patient specificity and accuracy. The current limitations of this technology are upfront investments and a lack of optimisation of materials. Conclusions: The use of 3D-printed ultrasound task trainers is in its infancy, and more research is needed to determine whether or not this technology will benefit medical learners in the future.
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.
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 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it