vishwas1234567/2019_aarhus_critical_data

Tutorials for the 2019 Aarhus Datathon

Aarhus Critical Care Datathon 2019

Data Access

Participants of the Datathon are added to the Google Group aarhus-critical-2019-participants. Members of this group have access to computation resources through the Google Cloud Platform (GCP) project aarhus-critical-2019-team and to datasets via the GCP project physionet-data.

You can access the datasets directly on GCP:

1. Create a free account on GCP

2. Open aarhus-critical-2019-team in the console

3. Open BigQuery

4. Run a query. E.g. count the number of hospital admissions:

   SELECT count(*)
   FROM `physionet-data.mimiciii_clinical.admissions` 

Tutorial Notebooks

You can open the following tutorial notebooks on Colab and get started instantly. Requirements for these notebooks are: (1) you have a Google account, and (2) your Google account has been added to the aarhus-critical-2019-participants Google group.

eICU-CRD

• 01-accessing-the-data.ipynb
• 02-explore-patients.ipynb
• 03-severity-of-illness.ipynb
• 04-summary-statistics.ipynb
• 05-prediction.ipynb

MIMIC-III

• mimic-iii-tutorial-aarhus.ipynb

MIMIC-CXR

• mimic-cxr-train-aarhus.ipynb

R

Datasets can also be queried directly from R. This is exemplified in the following R markdown notebook: mimic-iii-los-aarhus.Rmd

Accessing MIMIC-CXR

The dataset used in the MIMIC-CXR tutorial is preprocessed for optimal use with Tensorflow. If you use a different library or just want a simpler representation of the data, the MIMIC-CXR dataset is available as JPEG images and CSV tables in the following GCP bucket: gs://physionet-data-mimic-cxr-jpg. The URL for the bucket is https://console.cloud.google.com/storage/browser/physionet-data-mimic-cxr-jpg