Exploring temporal patterns in emergency department triage notes with topic models

Topic modeling is an unsupervised machine- learning task of discovering topics, the underlying thematic structure in a text corpus. Dynamic topic models are capable of analysing the time evolution of topics. This paper explores the application of dynamic topic models on emergency department triage notes to identify particular types of disease or injury events, and to detect the temporal nature of these events.