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Comorbidity scores and machine learning methods can improve risk assessment in radical cystectomy for bladder cancer: research report

BACKGROUND: Pre-operative risk assessment in radical cystectomy (RC) is an ongoing challenge especially in elderly patients. OBJECTIVE: To evaluate the ability of comorbidity indices and their combination with clinical parameters in machine learning

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Bibliographic Details
Main Authors: Wessels, Frederik (Author) , Bußoff, Isabelle (Author) , Adam, Sophia (Author) , Kowalewski, Karl-Friedrich (Author) , Neuberger, Manuel (Author) , Nuhn, Philipp (Author) , Michel, Maurice Stephan (Author) , Kriegmair, Maximilian (Author)
Format: Article (Journal)
Language:English
Published: 03 June 2022
In: Bladder cancer
Year: 2022, Volume: 8, Issue: 2, Pages: 155-163
ISSN:2352-3735
DOI:10.3233/BLC-211640
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.3233/BLC-211640
Verlag, kostenfrei, Volltext: https://content.iospress.com/articles/bladder-cancer/blc211640
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Author Notes:Frederik Wessels, Isabelle Bußoff, Sophia Adam, Karl-Friedrich Kowalewski, Manuel Neuberger, Philipp Nuhn, Maurice S. Michel and Maximilian C. Kriegmair
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Summary:BACKGROUND: Pre-operative risk assessment in radical cystectomy (RC) is an ongoing challenge especially in elderly patients. OBJECTIVE: To evaluate the ability of comorbidity indices and their combination with clinical parameters in machine learning
Item Description:Gesehen am 06.08.2024
Physical Description:Online Resource
ISSN:2352-3735
DOI:10.3233/BLC-211640

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