Virtual Reality Technology and Remote Digital Application for Tele-Simulation and Global Medical Education: An Innovative Hybrid System for Clinical 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
Objective. Although simulation-based medical education is fundamental for acquisition and maintenance of knowledge and skills; simulators are often located in urban centers and they are not easily accessible due to cost, time, and geographic constraints. Our objective is to develop a proof-of-concept innovative prototype using virtual reality (VR) technology for clinical tele simulation training to facilitate access and global academic collaborations. Methodology. Our project is a VR-based system using Oculus Quest as a standalone, portable, and wireless head-mounted device, along with a digital platform to deliver immersive clinical simulation sessions. Instructor’s control panel (ICP) application is designed to create VR-clinical scenarios remotely, live-stream sessions, communicate with learners and control VR-clinical training in real-time. Results. The Virtual Clinical Simulation (VCS) system offers realistic clinical training in virtual space that mimics hospital environments. Those VR clinical scenarios are customizable to suit the need, with high-fidelity lifelike characters designed to deliver interactive and immersive learning experience. The real-time connection and live-stream between ICP and VR-training system enables interactive academic learning and facilitates access to tele simulation training. Conclusions. VCS system provides innovative solutions to major challenges associated with conventional simulation training such as access, cost, personnel, and curriculum. VCS facilitates the delivery of academic and interactive clinical training that is similar to real-life settings. Tele-clinical simulation systems like VCS facilitate necessary academic-community partnerships, as well as global education network between resource-rich and low-income countries.
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 | 0.004 |
| 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 it