Interactive Cohort Analysis and Hypothesis Discovery by Exploring Temporal Patterns in Population-Level Health Records
Tianyi Zhang, Thomas H. McCoy, Roy H. Perlis, Finale Doshi‐Velez, Elena Leah Glassman · 2021
It is challenging to visualize temporal patterns in electronic health records (EHRs) due to the high volume and high dimensionality of EHRs. In this paper, we conduct a formative study with three clinical researchers to understand their needs of exploring temporal patterns in EHRs. Based on those insights, we develop a new visualization interface that renders medical event trajectories in a holistic timeline view and guides users towards interesting patterns using an information scent based method. We demonstrate how a clinical researcher can use our tool to discover interesting sub-cohorts with unique disease progression and treatment trajectories in a case study.