DataPulse: An Interactive Dashboard for Statistical and Exploratory Analysis of Multimodal Healthcare Data in Shiny

Adam Urban, James Connolly, Gauri Vaidya, Krishn Kumar Gupt, Meghana Kshirsagar

Abstract: The extraction of actionable insights from data-driven analyses is crucial for efficiently profiling, analyzing, and visualizing intricate medical datasets. A robust, generic data profiling tool is essential to uncover and understand relationships within medical data. In this context, building Shiny app can lead to numerous advantages—providing interactive, user-friendly, and dynamic dashboards, and the capacity to deploy scalable, web-based solutions. In this article, we introduce DataPulse, a versatile data profiling tool designed to analyze multimodal healthcare data. By leveraging advanced statistical methodologies, DataPulse uncovers complex relationships in the data and displays them through comprehensive dashboards. For instance, in ra-diogenomics, sequential imaging visualizations can highlight dynamic changes in disease progression over time. The article discusses two usecases of DataPulse: one focusing on the analysis of hip fracture patient pathways in the emergency depart

External IDs:dblp:conf/data/UrbanCVG025