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Sensitivity and Specificity Calculator — result sheet
Summarize all four cells of a binary classification table with sensitivity, specificity, accuracy, and prevalence.
Inputs used
Results
Visual chart
Breakdown
Calculation steps
Returned data table
Formula and methodology
Formula: sensitivity=TP/(TP+FN); specificity=TN/(TN+FP); accuracy=(TP+TN)/N; prevalence=(TP+FN)/N.
The four counts describe different denominators: actual positives, actual negatives, and all cases. Reporting the metrics together prevents accuracy from hiding an imbalanced reference set.
This result follows the calculator's declared inputs, precision, validation boundaries, and model limits.
Input contract
- True positives — minimum 0; maximum 1000000000
- False negatives — minimum 0; maximum 1000000000
- True negatives — minimum 0; maximum 1000000000
- False positives — minimum 0; maximum 1000000000
Worked example
| Input | Value |
|---|---|
| True positives | 90 |
| False negatives | 10 |
| True negatives | 180 |
| False positives | 20 |
Sensitivity: 90%; specificity: 90%; accuracy: 90%; prevalence: 30%.
Assumptions and limits
- All counts are nonnegative whole-number outcomes from one defined binary classification table.
- There must be at least one actual positive, one actual negative, and one total case for every requested metric.
- These descriptive metrics do not establish clinical utility, causal validity, or deployment safety.
Calculator note
Source and methodology
Use the official WorldCalculate methodology policy for the source, formula, precision, and boundary standards behind this calculator.
Planning estimate, not financial, medical, legal, or professional advice. © WorldCalculate — reuse with attribution. Built and curated by Hassan ALRowaie.
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