WiDS (Women in Data Science) Datathon 2020: ICU Mortality Prediction 1.0.0

File: <base>/README.md (1,449 bytes)
# WiDS Datathon 2020

In advance of the March 2, 2020 Global Women in Data Science (WiDS) Conference, we invite you to build a team, hone your data science skills, and join us in a predictive analytics challenge focused on social impact. Register at bit.ly/WiDSdatathon2020!

The WiDS Datathon 2020 focuses on patient health through data from MIT’s GOSSIS (Global Open Source Severity of Illness Score) initiative. Brought to you by the Global WiDS team, the West Big Data Innovation Hub, and the WiDS Datathon Committee, this year’s datathon is open until February 24, 2020. Winners will be announced at the WiDS Conference at Stanford University and via livestream, reaching a community of 100,000+ data enthusiasts across more than 50 countries.

## File descriptions

To download the following files, please visit the challenge site: https://bit.ly/WiDSdatathon2020kaggle

- training_v2.csv: the training data. You should see 91,713 encounters represented here. Please view the WiDS Datathon 2020 Dictionary file for more information about the columns.
- unlabeled.csv: the data without hospital_death provided. You are being asked to predict the hospital_death variable for these encounters.
- samplesubmission.csv: a sample submission file in the correct format
- solution_template.csv: a list of all the rows (and encounters) that should be in your submissions
- WiDS Datathon 2020 Dictionary.csv: supplemental information about the data