Neuroimaging to guide neuroprognostication in the neonatal intensive care unit
Bibliographic record
Abstract
PURPOSE OF REVIEW: Neurological problems are common in infants admitted to the neonatal intensive care unit (NICU). Various neuroimaging modalities are available for neonatal brain imaging and are selected based on presenting problem, timing and patient stability. RECENT FINDINGS: Neuroimaging findings, taken together with clinical factors and serial neurological examination can be used to predict future neurodevelopmental outcomes. In this narrative review, we discuss neonatal neuroimaging modalities, and how these can be optimally utilized to assess infants in the NICU. We will review common patterns of brain injury and neurodevelopmental outcomes in hypoxic-ischemic encephalopathy, perinatal arterial ischemic stroke and preterm brain injury. SUMMARY: Timely and accurate neuroprognostication can identify infants at risk for neurodevelopmental impairment and allow for early intervention and targeted therapies to improve outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".