Article
A machine learning-based prediction model of H3K27M mutations in brainstem gliomas using conventional MRI and clinical features.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology - 1 Jan 2019
Pan Chang-Cun, Liu Jia, Tang Jie, Chen Xin, Chen Fang, Wu Yu-Liang, Geng Yi-Bo, Xu Cheng, Zhang Xinran, Wu Zhen, Gao Pei-Yi, Zhang Jun-Ting, Yan Hai, Liao Hongen, Zhang Li-Wei
Abstract excerpt
BACKGROUND: H3K27M is the most frequent mutation in brainstem gliomas (BSGs), and it has great significance in the differential diagnosis, prognostic prediction and treatment strategy selection of BSGs. There has been a lack of reliable noninvasive methods capable of accurately predicting H3K27M mutations in BSGs. METHODS: A total of 151 patients with newly diagnosed BSGs were included in this retrospective...
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