Non-linear missing data imputation for healthcare data via index-aware autoencoders

Author:

Kabir Sadaf,Farrokhvar Leily

Publisher

Springer Science and Business Media LLC

Subject

General Health Professions,Medicine (miscellaneous)

Reference57 articles.

1. Abiri N, Linse B, Edén P, Ohlsson M (2019) Establishing strong imputation performance of a denoising autoencoder in a wide range of missing data problems. Neurocomputing 365:137–146

2. Al-Helali B, Chen Q, Xue B, Zhang M (2018) A hybrid gp-knn imputation for symbolic regression with missing values. In: Australasian joint conference on artificial intelligence. Springer, pp 345–357

3. Al-Shayea QK (2011) Artificial neural networks in medical diagnosis. Int J Comput Sci Issues 8 (2):150–154

4. Baldi P (2012) Autoencoders, unsupervised learning, and deep architectures. In: Proceedings of ICML workshop on unsupervised and transfer learning, pp 37–49

5. Batista GE, Monard MC, et al. (2002) A study of k-nearest neighbour as an imputation method. HIS 87(251-260):48

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