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决策树用于评估患多发性硬化症的风险.

Manuela Pasella1, Fabio Pisano1, Barbara Cannas1

  • 1Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, Italy.

Frontiers in neuroinformatics
|August 31, 2023
PubMed
概括

一个新的机器学习模型使用免疫遗传标记来预测多发性硬化症 (MS) 风险. 这种工具可以帮助识别有风险的个体,并监测多发性硬化症患者的家属.

关键词:
决策树 决策树是一个决定树.人类白细胞抗原.免疫遗传风险标志物 免疫遗传风险标志物多发性硬化发展的可能性.机器学习是机器学习.多个分类器的多重分类器多发性硬化症 多发性硬化症

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Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
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