Acute Kidney Injury (AKI) is associated with high morbidity and hospital readmission, which has caused
tremendous burden to the society. The current AKI Clinical Decision Support System (CDSS) has shown potentials
of improving clinical outcomes. However, it has limitations that needs to be addressed. We propose an innovative
approach to improve the current AKI CDSS by incorporating a DNN predictive model to provide real-time
prediction of AKI, as well as a new design of the medical alert to further enhance the usability of the system.

Authors:

YiFan Wu (Presenter)
University of Washington

Cong Zhu, Universirty of Texas Health Science Center at Houston