Perspectives on Remote Robotic-Assisted Stroke Treatment: A Commentary Paper
Bibliographic record
Abstract
The proved feasibility of robotic-assisted endovascular treatment of intracranial aneurysms has stimulated the idea of a potential application of remote robotics for the treatment of acute ischemic stroke. The possibility of developing a more advanced remote-controlled robotic system capable of performing a complete mechanical thrombectomy procedure would help bridge the health care gap of lack of technical expertise in isolated areas. This possibility could allow a more equitable access to mechanical thrombectomy to a larger number of patients and be a breakthrough for acute ischemic stroke care worldwide. Many aspects around the technical, human, financial, and regulatory requirements should be discussed to implement remote robotic-assisted procedures. In this State of Practice article, we aimed to outline the major challenges that must be considered, as well as proposed solutions. However, different solutions may be applied in different health care systems on the basis of the availability of human and financial resources.
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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 | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.025 | 0.028 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".