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https://github.com/aidh-ms/hirid_v1

https://github.com/aidh-ms/hirid_v1

Science Score: 13.0%

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    Found 4 DOI reference(s) in README
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  • Host: GitHub
  • Owner: aidh-ms
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Fork of HIRID/HiRID_v1
Created about 3 years ago · Last pushed almost 6 years ago

https://github.com/aidh-ms/HiRID_v1/blob/master/ 

# HiRID - high time resolution ICU data set

HiRID is a **freely accessible** critical care dataset containing data relating to more than 34 thousand patient admissions to the Department of Intensive Care Medicine of the Bern University Hospital, Switzerland (ICU), an interdisciplinary 60-bed unit admitting >6,500 patients per year. The ICU offers the full range of modern interdisciplinary intensive care medicine for adult patients. The dataset was developed in cooperation between the Swiss Federal Institute of Technology (ETH) Zrich, Switzerland and the ICU.

The dataset contains de-identified demographic information and a total of 712 routinely collected physiological variables, diagnostic test results and treatment parameters from more than 34 thousand admissions during the period from January 2008 to June 2016. Data is stored with a uniquely high time resolution of one entry every two minutes.

# Data access

Find all information on data access at [hirid.intensivecare.ai](http://hirid.intensivecare.ai).

# Acknowledgement

If you use HiRID in your work,  please cite the following paper

> *Early prediction of circulatory failure in the intensive care unit using machine learning.*

- **Stephanie L. Hyland, Martin Faltys, Matthias Hser, Xinrui Lyu, Thomas Gumbsch**, Cristbal Esteban, Christian Bock, Max Horn, Michael Moor, Bastian Rieck, Marc Zimmermann, Dean Bodenham, **Karsten Borgwardt, Gunnar Rtsch, Tobias M. Merz**. Nature Medicine (2020).

    [https://doi.org/10.1038/s41591-020-0789-4](https://doi.org/10.1038/s41591-020-0789-4). Joint first and last authors are marked in bold font.

# Contact

You can contact us at hirid@intensivecare.ai

Owner

  • Name: AIDH MS
  • Login: aidh-ms
  • Kind: organization
  • Email: christian.porschen@ukmuenster.de
  • Location: Germany

Anaesthesiology and Intensive Care Digital Health Münster

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