Bibliographic record
Abstract
PURPOSE OF REVIEW: The purpose of this review is to provide an update on advanced neuroimaging techniques in traumatic brain injury (TBI). We will focus this review on recent literature published within the last 18 months and the advanced neuroimaging techniques of perfusion imaging and diffusion tensor imaging (DTI). RECENT FINDINGS: In the setting of a moderate or severe acute closed head injury (Glasgow Coma Scale <13), the most appropriate neuroimaging study is a noncontrast computed tomography (CT) scan. In the setting of mild TBI, the indication for neuroimaging can be determined using the New Orleans Criteria or Canadian CT Head Rules or National Emergency X-Ray Utilization Study-II clinical criteria. Two advanced neuroimaging techniques that are currently being researched in TBI include perfusion imaging and DTI. Perfusion CT has a higher sensitivity for detecting cerebral contusions than noncontrast CT examinations. DTI is a sensitive at detecting TBI at the group level (TBI-group versus control group), but there is insufficient evidence to suggest that DTI plays a clinical role for diagnosing mild TBI at the individual patient level. SUMMARY: Future research in advanced neuroimaging techniques including perfusion imaging and DTI may improve the accuracy of the diagnosis and prognosis as well as improve the management of TBI.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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 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".