2020 News

New on PhysioNet: the HiRID critical care dataset

June 5, 2020

We are pleased to announce the release of the HiRID critical care dataset, developed as part of a collaboration between Bern University Hospital and the Swiss Federal Institute of Technology (ETH). HiRID is a freely accessible critical care dataset containing data relating to more than 33 thousand admissions to the Department of Intensive Care Medicine of the Bern University Hospital, Switzerland, an interdisciplinary 60-bed unit admitting >6,500 patients per year. 

Read more: https://physionet.org/content/hirid/

Significant delays are expected to applications for credentialed access to PhysioNet.

March 25, 2020

We are currently dealing with a high volume of applications for credentialed access to PhysioNet, so please expect significant delays in the review process. We are doing our best to deal with the waitlist quickly, handling applications in the order in which they are received. To help ensure that your application is successful, please remember to:

  • Include a copy of your CITI training report (not the certificate).
  • Remind your reference to reply promptly when contacted.
  • Check your application details are correct before submitting.

We apologize for the inconvenience. Please bear with us during this busy time!

Announcing the PhysioNet/​Computing in Cardiology Challenge 2020 on Classification of 12-lead ECGs

Feb. 10, 2020

We are delighted to announce the PhysioNet/Computing in Cardiology Challenge 2020 on Classification of 12-lead ECGs. 

For more information, see the Challenge website: https://physionetchallenges.github.io/2020/

Quick links for this year's Challenge can be found here:

More information will be posted on the website linked above (and eventually mirrored on physionet.org/challenge/2020 with a delay as it is available). Please check the Challenge forum for real time updates. Please also post questions and comments in the forum. However, if your question reveals information about your entry, then please email challenge [at] physionet.org. We may post parts of our reply publicly if we feel that all Challengers should benefit from the information contained in our responses. We will not answer emails about the Challenge to any other address.

Many thanks again for your continued support of this event and we hope you enjoy this year's challenge. 

Read more: https://physionetchallenges.github.io/2020/

MIMIC-CXR paper published!

News from: MIMIC-CXR Database v2.0.0.

Feb. 10, 2020

A journal article describing the MIMIC-CXR database was recently published in Scientific Data. The article provides detail regarding the collection, curation, and processing done in order to create the database. The article is open access and available online [1].

The database has also been preprocessed into compressed JPG format images, which have been made available on PhysioNet as the MIMIC-CXR-JPG Database. The database includes labels extracted from the free-text reports using publicly available tools. You can read more about the creation of this resource in our arXiv preprint [2].

Finally, we have created the mimic-cxr GitHub repository for collaborative code development on MIMIC-CXR [3]. The code used to generate MIMIC-CXR-JPG from MIMIC-CXR is available in the repository already. We welcome code contributions from all users, and we encourage discussion of the data via the GitHub issues.

[1] Johnson AE, Pollard TJ, Berkowitz SJ, Greenbaum NR, Lungren MP, Deng CY, Mark RG, Horng S. MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports. Scientific Data. 2019;6.

[2] Johnson AE, Pollard TJ, Greenbaum NR, Lungren MP, Deng C-Y, Peng Y, Lu Z, Mark RG, Berkowitz SJ, Horng S. MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs. arXiv preprint arXiv:1901.07042. 2019.

[3] https://github.com/MIT-LCP/mimic-cxr

Read more: https://www.nature.com/articles/s41597-019-0322-0

WiDS (Women in Data Science) Challenge Announced! Register your team by 24 February 2020

News from: WiDS (Women in Data Science) Datathon 2020: ICU Mortality Prediction v1.0.0.

Jan. 23, 2020

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. 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.

WiDS Challenge 2020

Read more: https://physionet.org/content/widsdatathon2020/1.0.0/