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Updated: Sep 19, 2025

A Data-Driven Approach to Quantifying Immune States in Sepsis
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SASWISE-UE:通过可解释的可扩展组合进行细分和合成,用于不确定性估计

Weijie Chen1, Alan B McMillan2

  • 1Department of Electrical and Computer Engineering, University of Wisconsin-Madison, WI 53705, USA; Department of Radiology, University of Wisconsin-Madison, WI 53705, USA.

Computers in biology and medicine
|June 3, 2025
PubMed
概括

这项研究为可解释的医学深度学习模型提供了一个新的框架. 它使用不确定性图表来显示模型可靠性,改善对细分和合成任务的临床使用.

关键词:
组合学习学习 组合学习图像细分 图像细分 图像细分图像合成 图像合成医学图像 医学图像 医学图像不确定性估计估计不确定性

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