Epidemiologic information discovery from open-access COVID-19 case reports via pretrained language model

Wang, Zhizheng; Liu, Xiao Fan; Du, Zhanwei; Wang, Lin; Wu, Ye; Holme, Petter; Lachmann, Michael; Lin, Hongfei; Wong, Zoie S.Y.; Xu, Xiao-Ke; Sun, Yuanyuan

doi:10.1016/j.isci.2022.105079

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2023

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Cited by 2 publications

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“…This figure was taken from the original publication. 2 (A) The distribution of the F1 value for each named entity, which aggregates the results of five different named-entity-recognition methods, namely Lattice, 4 TENER, 5 GraphNER, 6 FLAT, 7 and our CCIE (denoted as “★”). The colored distributions correspond to different named entities; (B) the distribution of the F1 value for each text category, which aggregates the results of eight text classification methods, namely Transformer, 9 DPCNN, 10 FastText, 11 TextCNN, 12 TextRNN, 13 TextRCNN, 14 LSTM, 15 and our CCIE.…”

Section: Expected Outcomesmentioning

confidence: 99%