MR Imaging–Compatible Electroencephalography Electrode System for an Epilepsy Monitoring Unit
Bibliographic record
Abstract
We studied the usefulness of an MR imaging-compatible electroencephalography (EEG) electrode system for continuous EEG recordings in our epilepsy monitoring unit (EMU) by comparing 100 consecutive patients with MR imaging-compatible and MR imaging-incompatible EEG recording electrodes who underwent MR imaging between 3:00 pm and 7:00 am. The MR imaging-compatible system captured seizures in 21/50 (42%) patients and clinically valuable new electrographic data in 13/50 (26%) patients during the study interval, whereas possible seizures were lost to recording in 19/50 (38%) patients in the MR imaging-incompatible system. EEG recording was comparable by both systems, but the nurses could disconnect and reconnect the patients to their electrode cables only in the MR imaging-compatible system during the study interval while the EEG technologists were off duty. This study shows that the MR imaging-compatible system could be used routinely for long-term monitoring of the patients in EMUs.
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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 | 0.001 | 0.010 |
| 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) | 0.001 | 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 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".