Using Machine Learning and Feature Importance to Identify Risk Factors for Mortality in Pediatric Heart Surgery
The objective of this IRB-approved retrospective monocentric study was to identify risk factors for mortality after surgery for congenital heart defects (CHDs) in pediatric patients using machine learning (ML). CHD belongs to the most common congenital malformations, and remains the leading mortalit...
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Veröffentlicht in: | Diagnostics (Basel) 2024-11, Vol.14 (22), p.2587 |
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Sprache: | eng |
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Zusammenfassung: | The objective of this IRB-approved retrospective monocentric study was to identify risk factors for mortality after surgery for congenital heart defects (CHDs) in pediatric patients using machine learning (ML). CHD belongs to the most common congenital malformations, and remains the leading mortality cause from birth defects.
The most recent available hospital encounter for each patient with an age |
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ISSN: | 2075-4418 2075-4418 |
DOI: | 10.3390/diagnostics14222587 |