State of the Art Stroke Imaging: A Current Perspective
Bibliographic record
Abstract
Acute stroke is a widespread, debilitating disease. Fortunately, it also has one of the most effective therapeutic options available in medicine, endovascular treatment. Imaging plays a major role in the diagnosis of stroke and aids in appropriate therapy selection. Given the rapid accumulation of evidence for patient subgroups and concurrent broadening of therapeutic options and indications, it is important to recognize the benefits of certain imaging technologies for specific situations. An effective imaging protocol should: 1) be fast, 2) easily implementable, 3) produce reliable results, 4) have few contraindications, and 5) be safe, all with the goal of providing the patient the best chance of achieving a favorable outcome. In the following, we provide a review of the currently available imaging technologies, their advantages and disadvantages, as well as an overview of the future of stroke imaging. Finally, we offer a perspective.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 |
| 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 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".