ehrdata#

EHRData overview: an X data array with obs, var, and tem annotations, alongside layers, obsm, varm, obsp, varp, and uns.

EHRData is a data framework that comprises a FAIR storage format and a collection of Python libraries for performant access, alignment, and processing of uni- and multi-modal electronic health record datasets. This repository contains the core ehrdata library, which has the EHRData class at its heart. See the ehrapy package for an analysis package that uses ehrdata to enable the analysis of electronic health record datasetes.

Getting started#

EHRData extends AnnData to represent data of n observations × d variables × t time points — a natural fit for the time-resolved measurements found in electronic health records.

import ehrdata as ed

# Load the PhysioNet 2019 sepsis-prediction challenge dataset
# (downloaded and cached on first use)
edata = ed.dt.physionet2019()
edata

EHRData object with n_obs × n_vars × n_t = 40336 × 35 × 48
    obs: 'Age', 'Gender', 'Unit1', 'Unit2', 'HospAdmTime', 'training_Set'
    var: 'Parameter'
    tem: '0', '1', '2', ..., '45', '46', '47'
    shape of .X: (40336, 35, 48)

The 35 clinical parameters are stored over 48 hourly time steps in a single three-dimensional array, with patient- and variable-level metadata aligned alongside. You can slice across all three axes at once — for example, the 48-hour trajectory of the sepsis label for one patient:

edata[edata.obs.index == "p020378", edata.var_names == "SepsisLabel"].X

For more, please refer to the documentation, in particular the API documentation.

Disclaimer#

ehrdata is under heavy construction, and its API not stable. If you find it potentially interesting for your work, reach out to us via the scverse zulip platform! We can help you using it and will be able to stabilize things you need.

If you have inputs on features, please do not hesitate to open an issue on our issue tracker!

Installation#

You need to have Python 3.12 or newer installed on your system. If you don’t have Python installed, we recommend installing Mambaforge.

There are several alternative options to install ehrdata:

Install the latest release of ehrdata from PyPI:

pip install ehrdata

Install the latest development version:

pip install git+https://github.com/theislab/ehrdata.git@main

Release notes#

See the changelog.

Contact#

For questions and help requests, you can reach out in the scverse discourse. If you found a bug, please use the issue tracker.

Citation#

t.b.a

ehrdata

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