The repository consists of a number of Structured Query Language (SQL) scripts which build the MIMIC-III database in a number of systems and extract useful concepts from the raw data. Jupyter notebooks are also provided which detail analyses performed on MIMIC-III.
The repository is organized as follows:
- benchmark - Various speed tests for indices
- buildmimic - Scripts to build MIMIC-III in a relational database management system (RDMS), in particular postgres is our RDMS of choice
- concepts - Useful views/summaries of the data in MIMIC-III, e.g. demographics, organ failure scores, severity of illness scores, durations of treatment, easier to analyze views, etc. The paper above describes these in detail, and a README in the subfolder lists concepts generated.
- notebooks - A collection of R markdown and Jupyter notebooks which give examples of how to extract and analyze data
- notebooks/aline - An entire study reproduced in the MIMIC-III database - from cohort generation to hypothesis testing
- notebooks/aline-aws - As above, launchable immediately on AWS
- tests - You should always have tests!
- tutorials - Similar to the notebooks folder, but focuses on explaining concepts to new users
* A Makefile build system has been created to facilitate the building of the MIMIC database, and optionally contributed views from the community. Please refer to the Makefile guide for more details.