Machine-Learning Versus Traditional Scores for Predicting Outcomes After Coronary Artery Bypass Graft Surgery: A Systematic Review and Meta-Analysis.
- DOI
- 10.1177/15533506261468192
- Published
- 2026 Aug 5
- Container
- Surgical innovation
- Publisher
- Not recorded
- Open access
- unknown
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limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1177/15533506261468192,
title = {Machine-Learning Versus Traditional Scores for Predicting Outcomes After Coronary Artery Bypass Graft Surgery: A Systematic Review and Meta-Analysis.},
author = {Gupta AK and Zaka A and Tyagi D and Mutahar D and Parvez R and Muston B and Farag M and Lombardo A and Eranki A and Wilson-Smith A and Song G and Stretton B and Kovoor JG and Bacchi S and Ramponi F and Chan JCY and Zaman S and Chow C and Kovoor P and Bennetts JS and Maddern GJ},
year = {2026},
journal = {Surgical innovation},
doi = {10.1177/15533506261468192},
url = {https://doi.org/10.1177/15533506261468192}
}RIS
TY - JOUR TI - Machine-Learning Versus Traditional Scores for Predicting Outcomes After Coronary Artery Bypass Graft Surgery: A Systematic Review and Meta-Analysis. AU - Gupta AK AU - Zaka A AU - Tyagi D AU - Mutahar D AU - Parvez R AU - Muston B AU - Farag M AU - Lombardo A AU - Eranki A AU - Wilson-Smith A AU - Song G AU - Stretton B AU - Kovoor JG AU - Bacchi S AU - Ramponi F AU - Chan JCY AU - Zaman S AU - Chow C AU - Kovoor P AU - Bennetts JS AU - Maddern GJ PY - 2026 JO - Surgical innovation DO - 10.1177/15533506261468192 UR - https://doi.org/10.1177/15533506261468192 ER -
APA
AK, G., A, Z., D, T., D, M., R, P., B, M., M, F., A, L., A, E., A, W., G, S., B, S., JG, K., S, B., F, R., JCY, C., S, Z., C, C., P, K., JS, B., & GJ, M. (2026). Machine-Learning Versus Traditional Scores for Predicting Outcomes After Coronary Artery Bypass Graft Surgery: A Systematic Review and Meta-Analysis.. Surgical innovation. https://doi.org/10.1177/15533506261468192
Source records
- pubmed · retrieved 2026-11-10T12:09:05.148Z