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Clinical measures, radiomics, and genomics offer synergistic value in AI-based prediction of overall survival in patients with glioblastoma
- Source :
- Scientific Reports, Vol 12, Iss 1, Pp 1-13 (2022)
- Publication Year :
- 2022
- Publisher :
- Nature Portfolio, 2022.
-
Abstract
- Abstract Multi-omic data, i.e., clinical measures, radiomic, and genetic data, capture multi-faceted tumor characteristics, contributing to a comprehensive patient risk assessment. Here, we investigate the additive value and independent reproducibility of integrated diagnostics in prediction of overall survival (OS) in isocitrate dehydrogenase (IDH)-wildtype GBM patients, by combining conventional and deep learning methods. Conventional radiomics and deep learning features were extracted from pre-operative multi-parametric MRI of 516 GBM patients. Support vector machine (SVM) classifiers were trained on the radiomic features in the discovery cohort (n = 404) to categorize patient groups of high-risk (OS
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 12
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Scientific Reports
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.2e0a631fb2f84bd8ab1d9f8f31d56f26
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41598-022-12699-z