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Unsupervised Machine Learning Models Reveal Predictive Clinical Markers of Glioblastoma Patient Survival Using White Blood Cell Counts Prior to Initiating Chemoradiation

AuthID
P-010-2SY

Author(s)

Wang, WS

Kumm, ZT

Ho, CY

Zanesco-Fontes, I

Texiera, G

Reis, RM

Martinetto, H

Khan, J

McCandless, MG

Baker, KE

Anderson, MD

Chohan, MO

Beyer, S

Elder, JB

Giglio, P

Otero, JJ

Tipo de Documento

Article

Year published

2024

Publicado

in NEURO-ONCOLOGY ADVANCES, ISSN: 2632-2498

Volume: 6, Número: 1

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Publication Identifiers

DOI: 10.1093/noajnl/vdad140

Pubmed: 38405202

SCOPUS: 2-s2.0-85186199832

Wos: WOS:001172769800001

Source Identifiers

ISSN: 2632-2498

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Unsupervised Machine Learning Models Reveal Predictive Clinical Markers of Glioblastoma Patient Survival Using White Blood Cell Counts Prior to Initiating Chemoradiation

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Unsupervised Machine Learning Models Reveal Predictive Clinical Markers of Glioblastoma Patient Survival Using White Blood Cell Counts Prior to Initiating Chemoradiation

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