Work

GraphXplore: Visual exploration and accessible preprocessing of medical data

Year: 2024

Type: software-paper

Abstract: Data-driven medical research requires explainable, robust models that can handle the noisy, high-dimensional nature of electronic healthcare data while adequately communicating the results to physicians. Additionally, metadata sharing, and reproducible dataset preparation are needed to increase data quality and interoperability of privacy-sensitive patient data. In this work, we present GraphXplore, a tool for visual data exploration, automatic metadata extraction and data transformation. It enables explainable, easy-to-use exploratory data analysis paired with dataset preparation and metadata annotation accessible for physicians. The tool is implemented as a Python package and graphical user interface application tailored to the needs of medical researchers and modularly integrable into hospital data warehouse infrastructures.

Source: SoftwareX

DOI: 10.1016/j.softx.2024.101978

Authors: Louis Bellmann, Karl Gottfried, Philipp Breitfeld, Frank Ückert

Institutions: University Medical Center Hamburg-Eppendorf, Krebsregister Baden-Württemberg

Language: English

Topic: Data Visualization and Analytics

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $970

OpenAlex ID: W4404654131

Cites: 38

Cited by: 2

Related to: 10