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ISeeU: Visually interpretable deep learning for mortality prediction inside the ICU

Project description

A ConvNet trained on MIMIC-III data for mortality prediction inside the Intensive Care Unit. It uses a set of 22 predictors sampled during the first 48h of ICU stay to predict the probability of mortality. This set of predictors roughly corresponds to those used by the SAPS-II severity score

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Files for iseeu, version 0.1.2
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