Precision/Recall vs. Sensitivity/Specificity

Is there a useful relationship between precision and recall as defined in the video on skewed data and the statistical terms sensitivity (= prob(true positive)) and specificity(= prob(true neg))?

Let me quote this wikipedia section which speaks very well the difference between them and when one is used while the other isn’t.

Terminology in information retrieval
In information retrieval, the positive predictive value is called precision, and sensitivity is called recall. Unlike the Specificity vs Sensitivity tradeoff, these measures are both independent of the number of true negatives, which is generally unknown and much larger than the actual numbers of relevant and retrieved documents. This assumption of very large numbers of true negatives versus positives is rare in other applications.

Thanks! Very helpful.

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You are welcome Richard.