MedEx - Data Analytics for Medical Domain Experts in Real-Time.

Clinical Data Data Analysis Data Exploration Graphical User Interface HiGHmed Visualization

Journal

Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582

Informations de publication

Date de publication:
03 Sep 2019
Historique:
entrez: 5 9 2019
pubmed: 5 9 2019
medline: 14 9 2019
Statut: ppublish

Résumé

Translational research in the medical sector is dependent on clear communication between all participants. Visualization helps to represent data from different sources in a comprehensible way across disciplines. Existing tools for clinical data management are usually monolithic and technically challenging to set up, others require a transformation into specific data models while providing mostly non-interactive visualizations or being specialized to very particular use cases. Statistical programming languages (R, Julia) on the other hand offer great flexibility in data analytics, but are harder to access for clinicians with little to no programming expertise. Our software, the Medical Data Explorer (MedEx), aims to fill this gap as light-weight, intuitive, web-based solution with simple data import routes. We couple a modern dynamic web interface with an in-memory database solution for near real-time responsiveness. MedEx provides multiple visualization options (Scatterplot, correlation heatmap, bar chart, grouped boxplot, grouped histogram, coplot) to get an easy overview on the loaded data as well as to perform pattern discovery and elementary statistics. We demonstrate the utility of MedEx, by example, on data from the cardiology research warehouse of Heidelberg University Hospital. In summary, our tool empowers clinicians to conduct their own interactive exploratory data analysis.

Identifiants

pubmed: 31483266
pii: SHTI190818
doi: 10.3233/SHTI190818
doi:

Types de publication

Journal Article

Langues

eng

Pagination

142-149

Auteurs

Aljoscha Kindermann (A)

Klaus Tschira Institute for Integrative Computational Cardiology.
Department of Internal Medicine III, University Hospital Heidelberg.

Ekaterina Stepanova (E)

Center for Bioinformatics, Saarland University.

Hauke Hund (H)

Department of Internal Medicine III, University Hospital Heidelberg.

Nicolas Geis (N)

Department of Internal Medicine III, University Hospital Heidelberg.

Brandon Malone (B)

NEC Laboratories Europe.

Christoph Dieterich (C)

Klaus Tschira Institute for Integrative Computational Cardiology.
Department of Internal Medicine III, University Hospital Heidelberg.

Articles similaires

Selecting optimal software code descriptors-The case of Java.

Yegor Bugayenko, Zamira Kholmatova, Artem Kruglov et al.
1.00
Software Algorithms Programming Languages
Humans Adult Male Female Video Games

Exploring blood-brain barrier passage using atomic weighted vector and machine learning.

Yoan Martínez-López, Paulina Phoobane, Yanaima Jauriga et al.
1.00
Blood-Brain Barrier Machine Learning Humans Support Vector Machine Software
Cephalometry Humans Anatomic Landmarks Software Internet

Classifications MeSH