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20192026
most citedDynamic survival prediction in intensive care units from heterogeneous time series without the need for variable selection or pre-processing

2 citations · 2 across the 3 of their papers we have counts for

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cs.LG2019

Impact of novel aggregation methods for flexible, time-sensitive EHR prediction without variable selection or cleaning

Jacob Deasy, Ari Ercole, Pietro Liò

Dynamic assessment of patient status (e.g. by an automated, continuously updated assessment of outcome) in the Intensive Care Unit (ICU) is of paramount importance for early alerti…

cs.LG2019★ 2 cited

Dynamic survival prediction in intensive care units from heterogeneous time series without the need for variable selection or pre-processing

Jacob Deasy, Pietro Liò, Ari Ercole

We present a machine learning pipeline and model that uses the entire uncurated EHR for prediction of in-hospital mortality at arbitrary time intervals, using all available chart,…