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Background: Fluid overload (FO) in the intensive care unit (ICU) is common, serious, and may be preventable. Intravenous medications (including administered volume) are a primary cause for FO but are challenging to evaluate as a FO predictor given the high frequency and time-dependency of their use and other factors affecting FO. We sought to employ unsupervised machine learning methods to uncover medication administration patterns correlating with FO.

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Deputy Health Minister, Ministry of Health, Ankara, Turkiye.

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Patterns of diuretic titration during inpatient management of acute decompensated heart failure.

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