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Using Machine Learning and Feature Importance to Identify Risk Factors for Mortality in Pediatric Heart Surgery
5
Zitationen
8
Autoren
2024
Jahr
Abstract
ML methods, along with model explainability tools, can reveal interesting insights into mortality risk after surgery for CHD. The proposed analytical workflow can serve as a blueprint for translating the analysis into a federated setting that builds upon the infrastructure of the German Medical Informatics Initiative.
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