Table 2 RNN papers on de-identification of medical free text
From: Survey on RNN and CRF models for de-identification of medical free text
Author | F-measurea | Precisiona | Recalla |
|---|---|---|---|
Dernoncourt et al. 2017 [33] | 99.23 | 99.21 | 99.25 |
Jiang et al. 2017 [38] | 91.45 | 93.24 | 89.72 |
Kajiyama et al. 2018 [39] | 80.61 | Not provided | Not provided |
Kim et al. 2018 [40] | 95.73 | 97.04 | 94.45 |
Lee et al. 2016 [41] | 99.26 | 99.21 | 99.31 |
Lee et al. 2019 [42] | 89.00 | 90.88 | 87.2 |
Liu et al. 2017 [43] | 96.98 | 97.94 | 96.04 |
Madan et al. 2018 [44] | 95.92 | Not provided | Not provided |
Richter et al. 2019 [45] | 96.00 | 97.00 | 95.50 |
Shweta et al. 2016 [46] | 93.84 | 97.26 | 90.67 |
Trienes et al. 2020 [47] | 91.20 | 95.90 | 86.90 |
Yang et al. 2019 [48] | 96.46 | 97.97 | 94.98 |