These are training materials for the MIMIC Critical Care Database. The package includes:

• a demo version of MIMIC which can be quickly installed in the Firefox web browser with the SQLite Plugin.
• some sample SQL queries which can be used to query the MIMIC data
• an IPython Notebook which connects to the demo MIMIC database and allows analysis to be carried out using Python.

MIMIC-III is a widely-used, freely available dataset developed by the MIT Lab for Computational Physiology, comprising deidentified health data associated with >40,000 critical care patients. It includes demographics, vital signs, laboratory tests, medications, and more. Details are available on the MIMIC website: https://mimic.physionet.org/

During the workshop, you will:

• Learn about MIMIC-III, the publicly accessible critical care database
• Create a local version of MIMIC-III with a small sample of patients using the Firefox SQLite Plugin
• Explore the patient data using SQL
• Plot and analyse the data using Python
• Get inspiration for future research projects

If you are familiar with git, please clone this repository. If not, click the 'Download ZIP' button on the right and then unzip the materials onto your computer.

To create the database on your computer, you will need the Firefox SQLite Manager Add-on. Open Firefox, select "Add-ons" from the Tools menu, and then install SQLite Manager. To create the demo database, select "connect to database" from the menu and choose the data/mimicdata.sqlite file.

To analyse the data using IPython Notebook:

• If you already have Python and the Pip package manager, run pip install ipython
• If you are new to Python, we suggest installing the Anaconda package from https://www.continuum.io/downloads. Then run conda update ipython.

Once IPython is installed, run ipython notebook from the command line to open IPython Notebook, then open one of the notebook (.ipynb) files (for example, 01-example-patient-heart-failure.ipynb).

If after this workshop you would like to gain access to the full MIMIC-III dataset, which contains rich data for over 40,000 patients, please see: https://mimic.physionet.org/gettingstarted/access/

We hope to improve the workshop contents over time and we welcome your contributions. Please raise an issue and/or submit a pull request!