An Expert System Prototype for the Early Diagnosis of Pneumonia

In this paper, an expert system model prototype based on Bayesian networks is proposed, which makes it possible to provide assistance to a doctor in the early diagnosis of a disease such as “pneumonia”. We designed a static Bayesian network with five key variables to obtain the probabilistic inference of the resulting node that determines the presence or absence of disease in a patient. We consulted with medical experts when selecting and quantifying input and output variables. When constructing a Bayesian model and conducting scenario analysis for a better prognosis of the diagnosis, we consulted with the attending physicians.