Numerical method to measure velocity integration, stroke volume and cardiac output while rest: using 2D fluid-solid interaction model
Bibliographic record
Abstract
Development of knowledge of cardiovascular diseases and treatments strongly depends on understanding of hemodynamic measurements. Hemodynamic parameters, therefore, have been investigated using simulation-based methods. A two-dimensional model was applied for seven healthy subjects with echo-Doppler at rest. Echocardiography imaging was also utilized to gain the geometry of the aortic valve. Fluid-Structure Interaction (FSI) model was carried out, coupling an Arbitrary Lagrangian-Eulerian mesh. Pressure loads were used as boundary conditions on the valve's ventricular and aortic sides. Pressure loads used were the calculated brachial pressures plus differences between brachial, central and left ventricular pressures. The FSI model predicted the velocity integration, stroke volume and cardiac output over a range of heart rates while rest. Numerical results generally had a difference of 5.4 to 15.87% with Doppler results. Linear correlations between numerical and clinical approaches have been applied. This makes possible predictions achieved from the FSI model to be gained which are highly accurate (e.g. correlation factor r = 0.995, 0.990 and 0.990 for velocity integration, stroke volume and cardiac output, respectively). The obtained numerical results showed that numerical methods can be combined with clinical measurements to provide good estimates of patient specific hemodynamics for different subjects.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".