TIEVis: A visual analytics dashboard for temporal information extracted from clinical reports

Abstract

Clinical reports, as unstructured texts, contain important temporal information. However, it remains a challenge for natural language processing (NLP) models to accurately combine temporal cues into a single coherent temporal ordering of described events. In this paper, we present TIEVis, a visual analytics dashboard that visualizes event-timelines extracted from clinical reports. We present the findings of a pilot study in which healthcare professionals explored and used the dashboard to complete a set of tasks. Results highlight the importance of seeing events in their context, and the ability to manually verify and update critical events in a patient history, as a basis to increase user trust.