To reduce medical doctor's workload and democratize access to medical care, the automation of the evidence acquisition and diagnosis process has attracted increasing attention recently. However, most works proposed in the machine learning literature focus solely on improving the prediction accuracy of the patient's pathology. We argue that this objective is insufficient to ensure doctors' acceptability of the system. For doctors to trust the system recommendations, they need to understand how th…