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Updated: Jun 13, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

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一种可解释的机器学习方法用于急性冠状动脉综合征患者的风险分层

Xing-Yu Zhu1,2, Kai-Jie Zhang1, Xiao Li1

  • 1Graduate School of Hebei North University, Zhangjiakou, 075031, Hebei Province, China.

Heliyon
|September 12, 2024
PubMed
概括

这项研究开发了一种可解释的机器学习模型,用于预测经皮冠状动脉干预 (PCI) 后急性冠状动脉综合征 (ACS) 患者的重大心血管不良事件 (MACE). 随机森林模型可以在手术后一年内准确识别高风险患者.

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相关概念视频

Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
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