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A Novel Swarm Intelligence-Driven Feature Selection for Interpretable Machine Learning in GBM Overall Survival Analysis

2025-04-17

Abstract excerpt

<h4>Purpose</h4> In this study, we develop and validate an interpretable machine learning (ML) model that integrates a hybrid Swarm Intelligence (SI)–based feature selection method with Magnetic Resonance Imaging (MRI)-derived radiomic features (RFs) to estimate overall survival (OS) in Glioblastoma Multiforme (GBM) patients. This study seeks to enhance the generalizability of the developed prognostic model and it...

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Literature Corpus work
5e465d0b-0733-565c-ab63-8d630bbf78d4
DOI
10.1101/2025.04.16.25325927
Open publication

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A Novel Swarm Intelligence-Driven Feature Selection for Interpretable Machine Learning in GBM Overall Survival AnalysisDOI 10.1101/2025.04.16.25325927
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