Quantification of Myocardial Blood Flow Using Pet to Improve the Management of Patients With Stable Ischemic Coronary Artery Disease
Bibliographic record
Abstract
Cardiac PET has been evolving over the past 30 years. Today, it is accepted as a valuable imaging modality for the noninvasive assessment of coronary artery disease. PET has demonstrated superior diagnostic accuracy for the detection of coronary artery disease compared with single-photon emission computed tomography, and also has a well-established prognostic value. The routine addition of absolute quantification of myocardial blood flow increases the diagnostic accuracy for three-vessel disease and provides incremental functional and prognostic information. Moreover, the characterization of the vasodilator capacity of the coronary circulation may guide proper decision-making and monitor the effects of lifestyle changes, exercise training, risk factor modification or medical therapy for improving regional and global myocardial blood flow. This type of image-guided approach to individualized patient therapy is now attainable with the routine use of cardiac PET flow reserve imaging.
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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 | 0.000 | 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) | 0.000 | 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".