Catching broken hearts: pre-clinical detection of doxorubicin and trastuzumab mediated cardiac dysfunction in the breast cancer setting
Bibliographic record
Abstract
Although breast cancer is one of the leading causes of death in women worldwide, there is an overall improvement in the survival of this patient population. This is likely due to a combination of early detection through screening and awareness, improved targeted biological therapy, and an overall improvement in disease management. Despite the beneficial effects of the 2 anti-cancer drugs doxorubicin (DOX) and trastuzumab (TRZ) in women with breast cancer, development of cardiotoxicity is a major concern. The occurrence of left ventricular systolic dysfunction is unacceptably high in nearly 1 in 4 women treated with DOX+TRZ in the breast cancer setting. In this review, we explore the use of non-invasive cardiac imaging for the early detection of chemotherapy-mediated cardiotoxicity in women with breast cancer, in the hope of preventing end-stage heart disease in this cancer population.
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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 | 0.001 |
| 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".