This repository contains code for the experiments in the JAMIA paper, Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data by Tang et al. (2020). Please also refer to the main FIDDLE respository.
IMPORTANT NOTE: Due to updated versions of python and related packages (pandas etc.), it might be impossible to replicate the exact numerical results in the paper. Moreover, due to sheer size of the datasets, full processing requires a machine with many CPU cores and a very large RAM (at least 500GB for MIMIC-III, ~3TB for eICU). Therefore, we recommend the following options:
- To reproduce MIMIC-III results similar to that in the paper, we recommend running the latest version of FIDDLE on the data and updating the feature dimensions in the metadata files to match the extracted feature sets.
- To replicate MIMIC-III results reported in the paper, consider using the jamia-replication branch. We have made every attempt to derive the same set of features (~0.00001% difference) from the MIMIC-III data. To make this experiment suite more accessible, we have released preprocessed MIMIC-III and eICU features via PhysioNet (for use with code in the jamia-replication branch). Please download the datasets here: https://physionet.org/content/mimic-eicu-fiddle-feature/1.0.0/
Clone the repository and initialize the FIDDLE submodule:
git clone https://github.com/MLD3/FIDDLE-experiments.git
git submodule update --init --recursiveTo reproduce the experiments on MIMIC-III, use conda env create -f environment.yml to create a conda envionment named FIDDLE-env which uses python 3.7, and then follow the steps in README.