Predicting stroke severity of patients using interpretable machine learning algorithms

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: 1 Online-Ressource.

Language: Englisch

Bibliographic citation: Predicting stroke severity of patients using interpretable machine learning algorithms ; volume:29 ; number:1 ; day:14 ; month:11 ; year:2024 ; pages:1-23 ; date:12.2024
European journal of medical research ; 29, Heft 1 (14.11.2024), 1-23, 12.2024

Creator: Sorayaie Azar, Amir
Samimi, Tahereh
Tavassoli, Ghanbar
Naemi, Amin
Rahimi, Bahlol
Hadianfard, Zahra
Wiil, Uffe Kock
Nazarbaghi, Surena
Bagherzadeh Mohasefi, Jamshid
Lotfnezhad Afshar, Hadi

Contributor: SpringerLink (Online service)

DOI: 10.1186/s40001-024-02147-1

URN: urn:nbn:de:101:1-2502040922165.024688905634

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

Last update: 15.08.2025, 7:26 AM CEST

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Sorayaie Azar, Amir
Samimi, Tahereh
Tavassoli, Ghanbar
Naemi, Amin
Rahimi, Bahlol
Hadianfard, Zahra
Wiil, Uffe Kock
Nazarbaghi, Surena
Bagherzadeh Mohasefi, Jamshid
Lotfnezhad Afshar, Hadi
SpringerLink (Online service)

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Predicting stroke severity of patients using interpretable machine learning algorithms

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