A Belief Rule-Based Expert System to Assess Bronchiolitis Suspicion from Signs and Symptoms Under Uncertainty

Bronchiolitis is an acute viral infection of the bronchioles-a common disease that affects millions of children around the world. Clinically, the disease is suspected by observing the signs and symptoms. The signs and symptoms are difficult to measure with 100% certainty, which make suspecting Bronchiolitis inaccurate while suspecting severity level as well. So, the paper aims at designing and developing a Belief Rule-Based Expert System (BRBES), which can suspect Bronchiolitis under uncertainty and increase accuracy. Belief rule based inference methodology has been considered to develop the inference engine of the expert system while the belief rule base has been used to develop the knowledge-base. The reliability of the BRBES has been tested by using real patient data and compared with the expert opinion.