Digitalization in clinical settings using graph databases
Digitalization in clinical settings using graph databases
(Non-FAU Project)
Overall project:
Project leader:
Project members: ,
Start date: October 1, 2018
End date:
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Funding source: Bayerisches Staatsministerium für Wirtschaft, Landesentwicklung und Energie (StMWi) (seit 2018)
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Abstract
In clinical settings, different data is stored in different
systems. These data are very heterogeneous, but still
highly interconnected. Graph databases are a good fit for
this kind of data: they contain heterogeneous "data nodes"
which can be connected to each other. The basic question is
now if and how clinical data can be used in a graph
database, most importantly how clinical staff can profit
from this approach. Possible scenarios are a graphical user
interface for clinical staff for easier access to required
information or an interface for evaluation and analysis to
answer more complex questions. (e.g., "Were there similar
patients to this patient? How were they treated?")
Publications
Using Associative Classification and Odds Ratios for In-Hospital Mortality Risk Estimation
Workshop on Interpretable ML in Healthcare at International Conference on Machine Learning (ICML). (Online, July 23, 2021 - July 23, 2021)
Open Access: https://www.cse.cuhk.edu.hk/~qdou/public/IMLH2021_files/15_CameraReady_OddsRatios.pdf
URL: https://sites.google.com/view/imlh2021/program
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