Optimizing cancer classification: a hybrid RDO-XGBoost approach for feature selection and predictive insights

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: 1 Online-Ressource.

Language: Englisch

Bibliographic citation: Optimizing cancer classification: a hybrid RDO-XGBoost approach for feature selection and predictive insights ; volume:73 ; number:12 ; day:9 ; month:10 ; year:2024 ; pages:1-14 ; date:12.2024
Cancer immunology immunotherapy ; 73, Heft 12 (9.10.2024), 1-14, 12.2024

Creator: Yaqoob, Abrar
Verma, Navneet Kumar
Aziz, Rabia Musheer
Shah, Mohd Asif

Contributor: SpringerLink (Online service)

DOI: 10.1007/s00262-024-03843-x

URN: urn:nbn:de:101:1-2502040910363.090893561372

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

Last update: 15.08.2025, 7:32 AM CEST

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Yaqoob, Abrar
Verma, Navneet Kumar
Aziz, Rabia Musheer
Shah, Mohd Asif
SpringerLink (Online service)

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Optimizing cancer classification: a hybrid RDO-XGBoost approach for feature selection and predictive insights

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