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Updated: Jun 4, 2025

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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肺癌患者患有并发症的存活率预后-一个高斯的贝叶斯网络模型

Shih-Hsien Tseng1, Kung-Min Wang1,2, Ting-Yang Su1

  • 1Department of Industrial Management, National Taiwan University of Science and Technology (NTUST), No.43, Sec. 4, Keelung Rd., Da'an Dist., Taipei, 106, Taiwan, ROC.

Medical & biological engineering & computing
|December 18, 2024
PubMed
概括

这项研究开发了一种条件高斯贝叶斯网络 (CGBN) 模型,用于预测肺癌生存时间,考虑糖尿病和肝脏疾病等并发症. 该模型提供了准确的预测,帮助为肺癌患者提供个性化治疗策略.

关键词:
伴随性疾病 伴随性疾病有条件的高斯贝叶斯网络.卡普兰·梅尔估计的估计.肺癌的生存率 肺癌的生存率

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