Simulation and Augmented Reality in Endovascular Neurosurgery
Bibliographic record
Abstract
Endovascular neurosurgery is a discipline strongly dependent on imaging. Therefore, technology that improves how much useful information we can garner from a single image has the potential to dramatically assist decision making during endovascular procedures. Furthermore, education in an image-enhanced environment, especially with the incorporation of simulation, can improve the safety of the procedures and give interventionalists and trainees the opportunity to study or perform simulated procedures before the intervention, much like what is practiced in the field of aviation. Here, we examine the use of simulators in the training of fighter pilots and discuss how similar benefits can compensate for current deficiencies in endovascular training. We describe the types of simulation used for endovascular procedures, including virtual reality, and discuss the relevant data on its utility in training. Finally, the benefit of augmented reality during endovascular procedures is discussed, along with future computerized image enhancement techniques.
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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 | 0.000 |
| 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".