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Updated: Jun 9, 2025

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[基于机器学习的in-vivo电子磁共振谱分类和辐射剂量预测研究]

Guangwei Xiong1,2, Bo Chen1,2, Lei Ma1,3

  • 1Institute of Radiation Medicine, Academy of Military Medical Sciences, Academy of Military Sciences, Beijing 100850, P. R. China.

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
|October 27, 2024
PubMed
概括

这项研究引入了机器学习,用于快速的,非侵入性的辐射剂量评估,使用in-vivo电子磁共振 (EPR). 使用支持矢量机器 (SVM) 和基因算法优化神经网络 (GA-BPNN) 的自动化分析可以提高核紧急情况的准确性和效率.

关键词:
优化神经网络的遗传算法在活体中,电子有磁共振.辐射剂量 辐射剂量 辐射剂量频谱的分类 频谱的分类支持矢量机器的支持矢量机器.

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