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Diastolic Function Evaluation: What Can We Learn From Machine Learning?
JACC: Cardiovascular Imaging ( IF 14.0 ) Pub Date : 2020-01-01 , DOI: 10.1016/j.jcmg.2019.07.028
Polydoros N Kampaktsis , Manolis Vavuranakis

We read with great interest the study by Lancaster et al. [(1)][1] regarding the use of a machine-learning algorithm for the unsupervised clustering of diastolic function variables. The authors reported improved prediction of clinical outcomes with machine learning over classification with the 2016

中文翻译:

舒张功能评估:我们可以从机器学习中学到什么?

我们非常感兴趣地阅读了Lancaster等人的研究。[(1)] [1]关于使用舒展功能变量的无监督聚类的机器学习算法。作者报告说,2016年通过机器学习而非分类改善了对临床结果的预测
更新日期:2020-02-03
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