Comparison of alarm strategies for continuous 12-lead ST-segment monitoring
Bibliographic record
Abstract
Several alarm detection strategies for real-time ST-segment monitoring (including detection using any single lead, any two leads, any two contiguous leads, any three leads, and STindex, computed as the sum of the absolute ST values from three quasi-orthogonal leads) have been evaluated using a 12-lead ST database generated from the Dalhousie PTCA database. The database includes 95 patients with a total of 202 balloon occlusions. For all the occluded vessels combined, the detection sensitivity using any single lead for ST-alarm detection decreases from 84.7% to 74.8% when the threshold is increased from 1 mm to 1.5 mm. For alarm detection using any two leads, two contiguous leads, and three leads, the results using a 1-mm threshold are 79.7%, 78.7%, and 77.2%, respectively. The two-lead performance results can be improved to 87.1% for any two leads and to 84.2% for any two contiguous leads if a lower threshold of 0.8 mm is used. For all the possible three-lead combinations, the STindex computed using leads III, V2, and V5 shows the highest correlation to the sum of the absolute ST values from all 12 leads. A detection sensitivity of 85.2% can be obtained using STindex with a threshold of 1.5 mm.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".