An architecture of open-source tools to combine textual information extraction, faceted search and information visualisation
This work addresses the problem of handling unstructured medical data for clinicians and researchers in hospitals or institutes, but it is incremental as it adapts existing tools to specific domains.
The authors tackled the integration of complex medical data into a clinical research database by developing an architecture using open-source tools for textual information extraction, faceted search, and visualization, showing it is suitable for nephrology and mammography with limited adaptations.
This article presents our steps to integrate complex and partly unstructured medical data into a clinical research database with subsequent decision support. Our main application is an integrated faceted search tool, accompanied by the visualisation of results of automatic information extraction from textual documents. We describe the details of our technical architecture (open-source tools), to be replicated at other universities, research institutes, or hospitals. Our exemplary use cases are nephrology and mammography. The software was first developed in the nephrology domain and then adapted to the mammography use case. We report on these case studies, illustrating how the application can be used by a clinician and which questions can be answered. We show that our architecture and the employed software modules are suitable for both areas of application with a limited amount of adaptations. For example, in nephrology we try to answer questions about the temporal characteristics of event sequences to gain significant insight from the data for cohort selection. We present a versatile time-line tool that enables the user to explore relations between a multitude of diagnosis and laboratory values.