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. 2010 Oct 1;7(Fall):1a.

Table 2.

Precision, Recall, Accuracy, and F-statistic for SQLServer (Sentence), SQLServer (Report), and NegEx

Fracture Status as Determined by Gold Standard
Positive Negative
Fractures identified by SQLServer (report) Positive 2 reportsa 0 reportsb Precision: 1.00
Negative 11 reportsc 387 reportsd Negative predictive value: 1.00
Accuracy: 0.97
Recall: 0.15 Specificity: 1.00 F-statistic: 0.26
Fractures identified by SQLServer (sentence) Positive 12 reportsa 0 reportb Precision: 1.00
Negative 1 reportsc 387 reportsd Negative predictive value: 0.99
Accuracy: 0.92
Recall: 0.92 Specificity: 1.00 F-statistic: 0.96
Fractures identified by NegEx Positive 13 reportsa 0 reportsb Precision: 1.00
Negative 0 reportsc 387 reportsd Negative predictive value: 1.00
Accuracy: 1.00
Recall: 1.00 Specificity: 1.00 F-statistic: 1.00

Notes:

Accuracy: (true positives + true negatives)/(true positives + true negatives + false positives + false negatives)

Precision: (true positives)/(true positives + false positives)

Recall: (true positives)/(true positives + false negatives)

Negative predictive value: (true negatives)/(true negatives + false negatives)

Specificity: (true negatives)/(true negatives + false positives)

F-statistic: 2 * (precision * recall)/(precision + recall)

a

true positives

b

false positives

c

false negatives

d

true negatives