Application of virtual reality ( <scp>VR</scp> ) technology for medical practitioners in type and screen (T&S) training
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
Abstract Nowadays, patients' safety is the top priority for medical services around the world. However, it is believed that many of the adverse events in hospitals are preventable. Type and screen (T&S) procedures require intense practical training by each medical practitioner in each hospital. This study applied an interactive Virtual Reality (VR) technology to supplement the traditional approach to facilitate procedural training. The VR system made use of the Unity3D for application development. To investigate the reliability and validity of the conceptual medical training model, a survey was conducted to measure the content, motivation and enhanced readiness of practitioners. The partial least squares (PLS) modelling was carried out to investigate the correlation between each pair of measured variables. The study results indicated that the learning model has good reliability for each measurement factor and validates the survey study. The PLS modelling also indicated a significant correlation between each pair of measured variables. The project developed a VR training program for training in T&S procedures. The study provides important implications on the development of a practical VR training program for medical practitioners, as well as valuable insights for the development of similar VR training programs 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 | 0.002 |
| 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 | 0.001 |
| 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