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Updated: Jul 29, 2026

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通过多式神经成像和机器学习预测质母细胞瘤的生存率

Patrick H Luckett1, Michael Olufawo2, Bidhan Lamichhane2,3

  • 1Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, 63110, USA. luckett.patrick@wustl.edu.

Journal of neuro-oncology
|September 5, 2023
PubMed
概括

机器学习使用治疗前的神经成像准确预测质母细胞瘤 (GBM) 的存活率. 这种方法确定了关键的大脑结构和功能预测因素,有助于疾病管理和患者护理.

关键词:
皮层厚度 皮层厚度深度学习是一种深度学习.功能性核磁共振成像 (MRI) 是一种功能性核磁共振成像.质母细胞瘤 (glioblastoma) 是一个幸存的生存方式

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