  In this article we provide a substantial discussion on the statistical
concept of conditional independence, which is not routinely mentioned in most
elementary statistics and mathematical statistics textbooks. Under the
assumption of conditional independence, an extended version of Bayes' Theorem
is then proposed with illustrations from both hypothetical and real-world
examples of disease diagnosis.
