Bayesian inference in the clinical diagnosis process: an educational approach to decision-making.

Abstract

The clinical diagnosis process involves executing a series of sequential steps. It begins with the formulation of a pre-test diagnostic probability, followed by the application of a diagnostic test, the result of which often improves the initially proposed probability, resulting in a post-test diagnostic probability. This process is an example of Bayesian inference, where diagnostic probabilities are calculated using equations derived from Bayes' theorem. This educational article provides a detailed explanation based on a real example of how to calculate the post-test diagnostic probability, following a Bayesian approach.