Article

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

2023-06-27

Abstract excerpt

<h4>Objective</h4> The challenge of irregular temporal data, which is particularly prominent for medication use in the critically ill, limits the performance of predictive models. The purpose of this evaluation was to pilot test integrating synthetic data within an existing dataset of complex medication data to improve machine learning model prediction of fluid overload. <h4>Materials and Methods</h4> This retrosp...

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Literature Corpus work: 9c594982-36f1-5561-9b76-0dd6dcfbee8f
DOI: 10.1101/2023.06.20.23291680

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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 unitDOI 10.1101/2023.06.20.23291680Read

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