Digitalization in clinical settings using graph databases
Digitalization in clinical settings using graph databases
(Non-FAU Project)
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Start date: October 1, 2018
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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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