Multimodal MRI radiomics based on habitat subregions of the tumor microenvironment for predicting risk stratification in glioblastoma

The integrated model combining clinicopathological data with a radiomic signature achieves good risk stratification and survival prediction in GBM and thus could be an important tool in clinical practice.

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Publication Details

Journal
PLoS ONE
Published
2025-06-27
DOI
https://doi.org/10.1371/journal.pone.0326361
Citations
5
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
6.80
Controls
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article

Multimodal MRI radiomics based on habitat subregions of the tumor microenvironment for predicting risk stratification in glioblastoma

Han Wang
5 citations
PLoS ONE
Radiomics and Machine Learning in Medical Imaging
6.80
article

Multimodal MRI radiomics based on habitat subregions of the tumor microenvironment for predicting risk stratification in glioblastoma

Han Wang
article en
5 citations

Abstract

The integrated model combining clinicopathological data with a radiomic signature achieves good risk stratification and survival prediction in GBM and thus could be an important tool in clinical practice.

PLoS ONEVol. 20(6)
Nanjing Drum Tower Hospital (CN)
Life in Land
Openalex Percentile: Top 3%
Radiomics and Machine Learning in Medical Imaging
6.80
DOIOpen Access PDFOpenAlex
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Multimodal MRI radiomics based on habitat subregions of the tumor microenvironment for predicting risk stratification in glioblastoma — Han Wang · PLoS ONE (2025) | TGRS Research Map | TGRS