Deep Learning-Based Radiomics for Prognostic Stratification of Low-Grade Gliomas Using a Multiple-Gene Signature

Low-grade gliomas are a heterogeneous group of infiltrative neoplasms. Radiomics allows the characterization of phenotypes with high-throughput extraction of quantitative imaging features from radiologic images. Deep learning models, such as convolutional neural networks (CNNs), offer well-performin...

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Autors principals:	Mert Karabacak, Burak B. Ozkara, Kaan Senparlak, Sotirios Bisdas
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2023-03-01
Col·lecció:	Applied Sciences
Matèries:	deep learning radiomics neural networks gliomas LGG gene signatures
Accés en línia:	https://www.mdpi.com/2076-3417/13/6/3873
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