SG HEALTHCARE AI
DATATHON & EXPO
Results for the Datathon
Datasets
Reminder: Teams need to apply and obtain access to the datasets they intend to use before the datathon.
1. Electrical Medical Records Datasets
During the datathon, teams will have access to 3 de-identified EMR datasets. Teams may choose to use one or all of these datasets to answer their clinical questions. In particular, these three datasets are: 1) the Medical Information Mart for Intensive Care (MIMIC)-IV Database from Physionet 2) the Philips eICU Collaborative Research Database (https://eicu-crd.mit.edu/). These three databases share similar data schemas. They contain hourly physiologic readings from bedside monitors, validated by ICU nurses. They also contain records of demographics, labs, nursing progress notes, discharge summaries, IV medications, fluid balance, and other clinical variables.
MIMIC-IV Dataset
Introduction & Access Application: https://mimic-iv.mit.edu/
Github repository: https://github.com/MIT-LCP/mimic-iv
Documentation: https://mimic-iv.mit.edu/docs/
When using this resource, please cite:
Johnson, A., Bulgarelli, L., Pollard, T., Horng, S., Celi, L. A., & Mark, R. (2020). MIMIC-IV (version 0.4). PhysioNet. https://doi.org/10.13026/a3wn-hq05.
Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215–e220.
eICU-CRD Dataset
Introduction & Documentation: https://eicu-crd.mit.edu/about/eicu/
Github repository: https://github.com/mit-eicu/eicu-code
Example code: https://github.com/mit-eicu/eicu-code/blob/master/concepts/icustay_detail.sql
When using this resource, please cite:
Pollard, T., Johnson, A., Raffa, J., Celi, L. A., Badawi, O., & Mark, R. (2019). eICU Collaborative Research Database (version 2.0). PhysioNet. https://doi.org/10.13026/C2WM1R.
Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215–e220.
We had 50 teams with close to 500 physicians and data scientists from more than 10 regions that joined us in our 2020 event!
SINGAPORE HEALTHCARE AI DATATHON AND EXPO 2021