I need help starting / understanding the calculations for the Bayes Network described below:

1. Bayes Network. Inoidenoes of diseast A and B (DA, .03} depend on the exposure (E) Disease A is additionally inuenced by risk factors {R}. Both diseases lead to symptoms (5) Results of the test for disease A (TA) are affected also by disease B. Positive test will be denoted as TA = 1.. negative as TA = (II. The Hayes Network is shown in Figure 1. Needed conditional probabilities are shown in Table l. 6'). Figure 1: The DAG of the Bayesian networks Table 1: The known (or elicited} conditional probabilities E 0 1 R 0 1 0.3 0.2 0.7 0.3 0 l 0.92 0.08 ago; 0.95 0.05 DEER 0.6 0.4 DDs 0.8 0.2 BABE 0.4 0.6 BABE 0.15 0135 DADB 0.1 0.9 DADB 0.03 0.9? [a] What is the probability of disease A (DA = 1}, if disease B is not present (D3 = 0).. but symptoms are present (3 = 1}. (b) What is the probability of exposure (E = 1), if symptoms are present (S = 1) and test is positive (T3 = 1}