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Precision

Definition
AI-generated

Precision (positive predictive value in binary diagnostic language) is the fraction of positive predictions that are true positives: TP / (TP + FP).

Topics
Probability and inference
Synonyms
Positive predictive value (when the positive prediction aligns with disease or case status)
Related
Classification Accuracy Area Under the ROC Curve (AUC) Calibration

Why it matters in GWAS

Polygenic or clinical risk classification at a chosen cutoff must be interpreted with prevalence and costs in mind; precision is central when follow-up resources apply only to those flagged high-risk.

Example usage

"At the recommended cutoff, screening scenario precision was 0.18, so most flagged individuals would not develop disease within five years."

Classification Accuracy Area Under the ROC Curve (AUC) Calibration Polygenic Risk Score (PRS) Recall Specificity
Related-term network

Click any node to open that term page.

Node order. The current term is first. Next come every page linked from Related terms, in the same top-to-bottom order as that list. Then new terms appear in two-hop layers: for each of those direct neighbors (in that same order), their related terms are appended if not already listed. A third pass does the same for two-hop nodes. The walk stops when a fixed maximum number of nodes is reached.

References

  • Powers DM. (2011). Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation. J Mach Learn Technol.
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