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Table 2 Comparison of detection performance

From: Detecting concept mentions in biomedical text using hidden Markov model: multiple concept types at once or one at a time?

    TP FP FN Prec. Rec. F-score
i2b2/VA Problem All-at-once 964 267 231 0.783 0.806 0.794
One-at-a-time 932 244 264 0.792 0.779 0.785
Test All-at-once 582 114 153 0.835 0.791 0.813
One-at-a-time 551 112 185 0.831 0.748 0.787
Treatment All-at-once 653 139 196 0.823 0.769 0.795
One-at-a-time 625 138 223 0.818 0.737 0.775
JNLPBA Protein All-at-once 2,373 840 653 0.739 0.784 0.761
One-at-a-time 2,251 752 775 0.749 0.744 0.747
DNA All-at-once 581 270 371 0.683 0.610 0.644
One-at-a-time 527 339 425 0.609 0.553 0.580
Cell Type All-at-once 496 167 174 0.748 0.740 0.744
One-at-a-time 455 168 215 0.730 0.678 0.703
Cell Line All-at-once 233 102 149 0.695 0.610 0.649
One-at-a-time 212 180 170 0.543 0.554 0.548
RNA All-at-once 36 24 59 0.594 0.383 0.462
One-at-a-time 33 18 62 0.640 0.345 0.447