Table 1.
Context type | TP | TN | FP | FN | Sensitivity | Specificity | Efficacy | Precision | Recall | F measure | Accuracy |
---|---|---|---|---|---|---|---|---|---|---|---|
Our pipeline with “PharmGKB” | 1,509 | 208 | 254 | 78 | 82.6 | 86.9 | 88.2 | 0.904 | 0.930 | 0.923 | 89.1 |
Our pipeline with “OMIM” | 2,225 | – | 79 | – | 78.0 | 77.5 | 81.8 | 0.600 | 0.681 | 0.764 | 59.3 |
Our pipeline with “CTD” | 1,776 | 153 | 375 | – | 70.7 | 65.5 | 72.2 | 0.729 | 0.803 | 0.801 | 79.7 |
Our pipeline with (“PharmGKB” AND “OMIM” AND “CTD”) | 1,875 | 102 | 275 | 75 | 82.3 | 84.4 | 93.3 | 0.896 | 0.852 | 0.828 | 94.7 |
PharmGKB corpus compared to that of our pipeline and the articles extracted in these datasets. The formulae used for calculating the accuracy of the proposed pipeline compared to the other datasets (ref. Supplementary Table 5 for detailed analysis).