Improving irregular temporal modeling by integrating synthetic data to the electronic medical record using conditional GANs: a case study of fluid overload prediction in the intensive care unit is a research paper published in medRxiv (2023). On theSindex it has a DataRank of 0. It has been cited 8 times.
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National Institutes of Health
Grant: 1R21HS028485-01A1
Machine learning validation of medication regimen complexity for critical care pharmacist resource prediction
National Institutes of Health
Grant: 5UL1TR002378-09
Georgia Clinical & Translational Science Alliance (Georgia CTSA)
National Institutes of Health
Grant: 5R01GM139967-03
Sepsis Physiomarkers for Appropriate Risk Knowledge of monitored patients in the ICU (SPARK-ICU)
National Institutes of Health
Grant: 3UL1TR002489-02S1
North Carolina Translational and Clinical Science Institute (NC TraCS)
National Institutes of Health
Grant: 5R01HS029009-02
Artificial intelligence-based health IT tools to optimize critical care pharmacist resources through adverse drug event prediction
NIGMS NIH HHS
Grant: R01 GM139967
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