Bayes's Theorem for Probability of Disease - Medical Algorithm

Prevalence of disease in population (enter from >0 to <100)

percent

Sensitivity of test for disease (enter from 0 to 100)

percent

Specificity of test for disease (enter from >0 to <100)

percent

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Data complete?

Prevalence of being disease free in population

Post-test probability that disease is present if there is a positive result

Post-test probability that disease is present if there is a negative result

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Caution: A qualified health practitioner should verify all results.
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Interpretation and Description

References

Next Steps in Evaluation

Other Testing
- Weight of Evidence
- Sensitivity and Specificity Calculator

Evaluation

Results

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MedicalAlgorithms.com APIs

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Interpretation and Description

References

Next Steps in Evaluation

Diagnosis

Objective

ICD-10

Bayes's Theorem

Purpose: To use Bayes's theorem to estimate the probability of disease in a patient being tested based on knowledge of prevalence and test performance.

Evaluation

Results

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MedicalAlgorithms.com APIs

Power Your Solutions with 5,000+ Automated Medical Analytics

Interpretation and Description

References

Next Steps in Evaluation

Diagnosis

Objective

ICD-10