Person in charge:
Software for medical training usually follows two types of approaches for the representation of its data. One type is the software of simulation-based training or virtual patients – which have highly structured representations of the clinical data and simulation plans. Another kind is some systems which focus on the narrative of a clinical case in free-text format – e.g., the Jacinto emergency medicine learning environment. In this case, the clinical data attaches to descriptions in an unstructured format. Thus, we propose a model for a hybrid narrative and clinical knowledge base for emergency medicine training that combines both of the approaches. We hypothesize that by connecting narratives with structured clinical information, we can take advantage of the strongest points of each method. On the one hand, structured clinical data offers flexibility for the production of case variations and alternative plans, which gives the machine more autonomy to assess user performance. On the other hand, free-text narratives enable the introduction of real scenario relevant aspects and context, beyond clinical data.
Emergency Medicine Training UML Model
The use of e-learning environments for medicine enables students to obtain better grades and achieve higher performance in a clinical emergency. However, essential tasks such as automatic assessment and derivation of existing cases, among others, are missing. We propose a novel architecture to accommodate these tasks, which uses a unique structure built on a case database and in an inference engine. To confirm the architecture applicability, we collected real-world cases from an e-learning environment to create the case database. We examined the combination of the case database and the inference engine. Obtained results enable to boost the system with the addition of new convenient functionalities in a reliable architecture.
Repositório da Produção Científica e Intelectual da Unicamp, May 19, 2017, UNICAMP, Campinas, SP, Brazil, 2017.
BTSym Proceedings, Springer, Campinas, SP, Brazil, 2016.