1. A method comprising: training a computer implemented Bayesian based diagnostic system, wherein training includes providing the diagnostic system with historical input data and a corresponding diagnosis to be derived from the historical input data and providing new input data having a predetermined diagnosis, wherein the diagnostic system generates a conditional probability table of a new diagnosis using the new input data; generating a confidence indicator corresponding to the new diagnosis, wherein the confidence indicator is generated on a per-diagnosis basis; comparing the confidence indicator to a predetermined threshold; using the diagnostic system to obtain another diagnosis using other input data in response to determining the confidence indicator of the new diagnosis is greater than a predetermined threshold, the another diagnosis including a corresponding accuracy measure; and generating a cumulative confidence indicator for multiple per-diagnosis confidence intervals, the cumulative confidence indicator including the determined confidence indicator.