Systematic evaluation of machine learning models for postoperative surgical site infection prediction.
<h4>Background</h4>Surgical site infections (SSIs) lead to increased mortality and morbidity, as well as increased healthcare costs. Multiple models for the prediction of this serious surgical complication have been developed, with an increasing use of machine learning (ML) tools.<h4&...
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Main Authors: | , , , , , , , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2024-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0312968 |
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