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Updated: Jun 25, 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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乳腺癌的临界风险评估,诊断和生存分析

Shamiha Binta Manir1, Priya Deshpande1

  • 1Department of EECE, Marquette University, Milwaukee, WI 53233, USA.

Diagnostics (Basel, Switzerland)
|May 24, 2024
PubMed
概括

这项研究使用机器学习来预测乳腺癌风险,诊断它,并使用三个数据集分析生存率. 机器学习模型,特别是随机森林和K-Nearest Neighbor,在改善乳腺癌检测和理解方面表现有前途.

关键词:
K-最近的邻居.逻辑回归的逻辑回归方法主要组件分析的主要组件分析随机的森林随机的森林在重新抽样时进行重新抽样.

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