Predicting acute kidney injury following open partial nephrectomy treatment using SAT-pruned explainable machine learning model

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1472-6947

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Predicting acute kidney injury following open partial nephrectomy treatment using SAT-pruned explainable machine learning model ; volume:22 ; number:1 ; day:16 ; month:5 ; year:2022 ; pages:1-7 ; date:12.2022
BMC medical informatics and decision making ; 22, Heft 1 (16.5.2022), 1-7, 12.2022

Creator: Lazebnik, Teddy
Bahouth, Zaher
Bunimovich-Mendrazitsky, Svetlana
Halachmi, Sarel

Contributor: SpringerLink (Online service)

DOI: 10.1186/s12911-022-01877-8

URN: urn:nbn:de:101:1-2022072023585550342221

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:32 AM CEST

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Lazebnik, Teddy
Bahouth, Zaher
Bunimovich-Mendrazitsky, Svetlana
Halachmi, Sarel
SpringerLink (Online service)

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Predicting acute kidney injury following open partial nephrectomy treatment using SAT-pruned explainable machine learning model

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Other Objects (12)

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