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. 2020 Apr 7;10:6026. doi: 10.1038/s41598-020-63159-5

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© The Author(s) 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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DeepMicro framework. An autoencoder is trained to map the input X to the low-dimensional latent space with the encoder and to reconstruct X with the decoder. The encoder part is reused to produce a latent representation of any new input X that is in turn fed into a classification algorithm to determine whether the input is the positive or negative class.