Prevention of myocardial infarctions, using non-invasive biophotonics measurement of biomarker cardiac troponin I.
Bibliographic record
Abstract
Coronary Heart Disease is the leading cause of death worldwide.Myocardial Infarctions are one of the most frequent cardiovascular diseases.The aim of this research is to design a non-invasive heart attack detection system based on biphotonic measurements.Several methods such as ECG monitoring, Florescence and Raman Spectroscopy are evaluated and Raman Spectroscopy is chosen due to advantages in sensitivity and efficiency.Since cTnI test is the current gold standard in diagnosing MI, the initial part of this research is based on a comprehensive study of this protein.In this research Raman spectra of cTnI is measured and after assessment of possible adjustments to noise level, SERS method is used to obtain the enhanced spectra and consequently a unique cTnI Raman signature.Due to low biological concentrations and low SNR, the spectra are measured in higher concentrations.Finally, a conceptual Raman design is proposed as a part of the instrumentation study of the system.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".