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Updated: Feb 8, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
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Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

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多任务诺莫格拉姆模型用于预测脑损伤中重出血和生存结果

Yan Pan1, Hao Xu2, Mengge Ye1,3

  • 1School of Basic Medical Sciences, Anhui Medical University, Hefei, 230032, China.

Journal of imaging informatics in medicine
|February 6, 2026
PubMed
概括

这项研究开发了一种使用CT扫描的多任务名图,用于预测脑患者的再出血和生存率. 该模型准确识别高风险个体,改善早期干预和患者的结果.

关键词:
深度转移学习 (DTL) 是一种深度转移学习.梯度加权类激活映射 (Grad-CAM) 的使用这个名字叫做Nomogram.重新出血的预测预测预测生存的预测.

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