MIMIC-III and eICU-CRD: Feature Representation by FIDDLE Preprocessing

This is a preprocessed dataset derived from patient records in MIMIC-III and
eICU, two large-scale electronic health record (EHR) databases. It contains
features and labels for 5 prediction tasks involving 3 adverse outcomes
(prediction times listed in parentheses): in-hospital mortality (48h), acute
respiratory failure (4h and 12h), and shock (4h and 12h). We extracted
comprehensive, high-dimensional feature representations (up to ~8,000
features) using FIDDLE ( **F** lex **I** ble **D** ata- **D** riven pipe
**L** in **E** ), an open-source preprocessing pipeline for structured
clinical data. These 5 prediction tasks were designed in consultation with a
critical care physician for their clinical importance, and were used as part
of the proof-of-concept experiments in the original paper to demonstrate
FIDDLE's utility in aiding the feature engineering step of machine learning
model development. The intent of this release is to share preprocessed MIMIC-
III and eICU datasets used in the experiments to support and enable
reproducible machine learning research on EHR data.