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Updated: Feb 4, 2026

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
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核心平均值匹配在空间分布变化下提高了风险估计

Egor Serov1, Diana Koldasbayeva2, Alexey Zaytsev1,3

  • 1Skolkovo Institute of Science and Technology, Moscow, Russia.

Scientific reports
|February 2, 2026
PubMed
概括

核心平均匹配 (KMM) 改进了空间数据中的机器学习风险估计,优于传统方法,如无权重 (NW) 和重要性权重 (IW). KMM提供了强大而准确的预测,对于面临分布转移的生态和医疗应用至关重要.

关键词:
分布转移的稳定性 分布转移的稳定性重新加权的重要性.核心平均值匹配的匹配空间建模 空间建模空间风险估计估计

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