QT interval measurement using RMED curve; a novel approach based on wavelet techniques
Bibliographic record
Abstract
HYPOTHESIS/OBJECTIVE: Prolonged QT interval is an index of propensity for dangerous ventricular tachyarrhythmias. The aim of this article is to establish an automatic algorithm for QT interval measurement. METHOD: The proposed method is based on the continuous wavelet transform. In this method, the concepts of the rescaled wavelet coefficients and dominant scales of the electrocardiogram (ECG) components are used to perform detection of ECG characteristic points. A new concept of rescaled maximum energy density is introduced so as to perform the estimation of the QT interval. RESULTS AND CONCLUSION: We have applied the algorithm to the PTB database of the Physiobank∖Physionet in lead II. Then, the results were evaluated using pertinent reference QT. The criterion used for evaluation of the method's performance is the root mean square (RMS) error. The method approached the RMS error of 27.89 ms for 549 subjects. The proposed method is fast, simple and is applicable to a wide range of ECG cardio cycle morphologies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".