GIDS for Chronic Disease Visualization: Implementation of Chronological Clustering as Workflow System

Abstract

Abstract-Chronic disease is linked to patient's' lifestyle. Therefore, doctor has to monitor his/her patient over time. This may involve reviewing many reports taken over short and long periods. Computer applications made it possible to visualize these reports on single displayer such as a timeline-based visualization tool. However, there is a limitation of studying the diabetes patient's history to find out what was the cause of the current development in patient's condition. In this paper, we propose a workflow system which uses the Grid-based Interactive Diabetes System (GIDS) to support diabetes analysis. Technically, the workflow uses an agglomerative clustering algorithm as clustering correlation algorithm which reduces the revision of long reports and focus on vital incidences. However, if doctor demands to review the full reports, the workflow displays the original reports. Through basic evaluation experiment, we were able to demonstrate the usability of the system as chronic patient's multi visualizer.