Classification and rule-based approach to diagnose pulmonary tuberculosis

Abstract

The pulmonary tuberculosis (TB) is diagnosed conventionally from the test results obtained from different medical examinations. The paper proposes a novel methodology using the classification technique called Identification tree (IDT) to diagnose TB computationally. The model reduces the number of parameters required for the diagnosis substantially. It also offers a list of rules for the speedy and easy diagnosis. The effectiveness of the method has been validated by comparing with existing techniques using standard detection measures. © 2011 Springer-Verlag.