Abstract: Methods and systems for explaining an output from a machine learning model. The methods include receiving from a machine learning model a probability score, a plurality of features, and a contribution value for each feature; transforming the plurality of features to a reduced number of features; generating at least one cluster of a portion of a population; grouping the patient in the generated cluster; and visually presenting to a user a comparison of the reduced number of features of the profile with the plurality of features associated with the portion of the population to explain the probability score.