Literature DB >> 30413952

Use of artificial neural networks to predict anterior communicating artery aneurysm rupture: possible methodological considerations.

Guido Adriaan de Jong1, René Aquarius2.   

Abstract

KEY POINTS: Use of algorithms to generate synthetic cases might result in a misrepresentation of the entire population. Training an artificial neural network with a mix of real and synthetic data might lead to non-realistic prediction precision.

Entities:  

Mesh:

Year:  2018        PMID: 30413952     DOI: 10.1007/s00330-018-5794-3

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  2 in total

1.  Prediction of rupture risk in anterior communicating artery aneurysms with a feed-forward artificial neural network.

Authors:  Jinjin Liu; Yongchun Chen; Li Lan; Boli Lin; Weijian Chen; Meihao Wang; Rui Li; Yunjun Yang; Bing Zhao; Zilong Hu; Yuxia Duan
Journal:  Eur Radiol       Date:  2018-02-23       Impact factor: 5.315

2.  Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric.

Authors:  Sabri Boughorbel; Fethi Jarray; Mohammed El-Anbari
Journal:  PLoS One       Date:  2017-06-02       Impact factor: 3.240

  2 in total

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