A probability principle set forth by Thomas Bayes; it is of value in medical decision-making and some of the biomedicalsciences. Bayes1 theorem is employed in clinical epidemiology to determine the probability of a particular disease in agroup of people with a specific characteristic on the basis of the overall rate of that disease and of the likelihood of thatspecific characteristic in healthy and diseased individuals, respectively. A common application of Bayes1 theorem is inclinical decision making where it is used to estimate the probability of a particular diagnosis given the appearance ofspecific signs, symptoms, or test outcomes. For example, the accuracy of the exercise cardiac stress test in predictingsignificant coronary artery disease (CAD) depends in part on the "pre-test likelihood" of CAD: the "prior probability" inBayes1 theorem. In Bayes1 theorem: the antecedent plausibility is termed the "prior probability", the likelihood of the currerdata given that particular hypothesis is called the "conditional probability", the rescaled values are called the "posteriorprobabilities".