Deep learning-based tumor segmentation and radiogenomic model for predicting EGFR amplification and assessing intratumoural heterogeneity in glioblastoma

Abstract Objectives To predict epidermal growth factor receptor (EGFR) amplification and explore the intratumoural heterogeneity of glioblastoma (GBM) using deep learning segmentation-based radiogenomics. Methods A total of 654 patients were included from multiple datasets, divided into a training c...

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מידע ביבליוגרפי

Principais autores:	Jianpeng Liu, Chuyun Shen, Shufan Jiang, Yanfei Wu, Jiaqi Tu, Yifang Bao, Haiqing Li, Na Wang, Ying Liu, Ji Xiong, Xueling Liu, Yuxin Li
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	SpringerOpen 2025-07-01
סדרה:	Journal of Big Data
נושאים:	Glioblastoma Epidermal growth factor receptor Deep learning Machine learning Radiogenomics
גישה מקוונת:	https://doi.org/10.1186/s40537-025-01221-7
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!