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. 2020 May 4;8(5):e17637. doi: 10.2196/17637

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©Zhichang Zhang, Lin Zhu, Peilin Yu. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 04.05.2020.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included.

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Multi-level representation learning for ER model. B-Sym: beginning of the noun phrase for the symptom entity; B-Test: beginning of the noun phrase for the test entity; C: input sentence; E: input embedding; I-Sym: middle of the noun phrase for the symptom entity; I-Test: middle of the noun phrase for the test entity; O: not a noun phrase; Trm: transform-block; y: output sentence’s predicted tag sequence.