Bias Cure supports transparent reasoning. It helps doctors and clinicians correctly interpret and communicate test results to their patients.
The chances of having a particular cancer, given a positive test result, are not *at all* the same as the chances of getting a positive test result, given a person has that cancer. This app cuts through that confusion and provides the former number, the probability the patient *really* wants to know.
Start with a possible "condition", add one or more test results, and watch the probability of having that condition update step by step. The app includes a an enlarged library of conditions and tests, but users also can enter any disease and diagnostic test manually and edit sensitivity and specificity values freely. The accuracy of the tests in the included library is backed by peer-reviewed research articles cited in the Validation Report, so users can go back to the original sources for more granular detail.
Bias Cure includes transparent sequential probability updating, individual 2x2 tables for test interpretation, a visual probability trend graph, and a printable validation PDF that shows the intermediate steps behind the final result along with source citations. Built-in Help pages explain Bayes' theorem, the 2x2 table, and how to enter and interpret test data.
Bias Cure is an educational and decision-support aid. It does not provide medical advice, does not replace clinical judgment, and should not be used as the sole basis for diagnosis or treatment decisions.