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一个新的深度机器学习算法,具有维度和大小缩小方法来消除特征:甲状腺癌诊断随机丢失数据

Onder Tutsoy1, Hilmi Erdem Sumbul2

  • 1Adana Alparslan Turkes Science and Technology University, Adana, Turkey.

Briefings in bioinformatics
|July 15, 2024
PubMed
概括

这项研究引入了一个深度学习算法,通过解决大数据和缺失信息的挑战来改善甲状腺癌诊断. 开发的方法实现了100%的训练准确性和83%的测试准确性在未见的数据.

关键词:
大数据就是大数据.深度学习是一种深度学习.缩小尺寸缩小尺寸的方法功能选择 功能选择缺失的数据 缺失的数据减小尺寸减小尺寸的减小方法甲状腺癌是一种癌症.

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相关概念视频

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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