Medical applications often require to capture the observed phenomenon dynamics, in order to properly support physicians' decision making. Case-based Reasoning (CBR), and more specifically case-based retrieval, is recently being recognized as a valuable decision support methodology in these domain. However, adopting CBR in this field is non trivial, since the need for describing the process dynamics impacts both on case representation and on the retrieval activity itself. In this work, we survey different methodologies introduced in the literature in order to implement medical CBR applications in time dependent domains, with a particular emphasis on time series representation and retrieval. Among the others, a novel approach, which relies on Temporal Abstractions, is analysed in depth.