Algorithm 2: Interpretability algorithm for training the dataset of the rules-based models

1. Input: the symptoms of the patient variable

2. Variables = the set of symptoms

/*3. For each symptom assign a relative weight*/

$Relativeweight=\frac{Weightofthevariable}{{\displaystyle \sum }Weightsofallvariables}$

/*4. Generate the probabilities of having the disease*/

−LR + = relative weights of the variables

+LR = 1 − (−LR)

5. Output: the positive and negative probabilities in addition to the relative weights of the variable

End