In medical process mining, specific domain characteristics have to be dealt with: in particular, in medicine, a significant amount of expert knowledge is typically available; moreover, an interactive approach, letting medical users be involved in the work of process model discovery, is more acceptable than a completely automated strategy. To this end, in our recent work we have defined SIM (Semantic Interactive Miner), an innovative process mining tool able to: (i) support the interaction with medical experts, who can progressively merge parts of the initially mined model, obtaining a more generalized version; (ii) exploit pre-encoded domain knowledge, to move from a model where activities are reported at the ground level to a more user-interpretable high-level version. In this paper we illustrate the features of our tool by showing its application to the case study of neonatal resuscitation simulation: we use SIM to mine the process models produced by two different groups of students of a simulation course, aiming at verifying whether differently skilled young professionals produce different processes, which can finally be compared to the correct guideline.