Latest News

Delays in reviewing applications for credentialed access

June 17, 2024

As a result of staffing changes in our research group, applications for credentialed access are likely to be subject to significant delays. 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.
  • Add an institutional or educational email address as your primary email.

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

George B. Moody PhysioNet Challenge 2024 is teaming up with Data Science Africa

May 18, 2024

The George B. Moody PhysioNet Challenge 2024 is teaming up with Data Science Africa (DSA) to innovate cardiac care through signal processing & machine learning at Nyeri, Kenya, for DSA's 10 year anniversary in June 2024.

DSA aims to create a hub in the network of data science researchers across Africa and strengthen the African data science community. #DSA2024Nyeri

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Guidelines for creating datasets and models from MIMIC

News from: MIMIC-IV v2.2.

April 24, 2024

We recognize that there is value in creating datasets or models that are either derived from MIMIC or which augment MIMIC in some way (for example, by adding annotations). Here are some guidelines on creating these datasets and models:

  • Any derived datasets or models should be treated as containing sensitive information. If you wish to share these resources, they should be shared on PhysioNet under the same agreement as the source data.
  • If you would like to use the MIMIC acronym in your project name, please include the letters “Ext” (for example, MIMIC-IV-Ext-YOUR-DATASET"). Ext may either indicate “extracted” (e.g. a derived subset) or “extended” (e.g. annotations), depending on your use case.

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Network issues at MIT, impacting the availability of PhysioNet

April 9, 2024

We are currently experiencing network issues at MIT, impacting the availability of PhysioNet services. We apologize for any inconvenience this may cause and are working to resolve the issue as soon as we can.

George B. Moody PhysioNet Challenge 2024: Challenge Update

March 14, 2024

We are delighted to announce that the George B. Moody PhysioNet Challenges are partnering with Data Science Africa (DSA) and the IEEE Signal Processing Society's Challenges and Data Collections Committee (CDCC). The IEEE CDCC is supporting this year’s Challenge with additional cash prizes for participating teams from Africa and the Challenge organizers will be running a workshop at this year's annual DSA meeting in Kenya. In connection with this, the Challenge organizers will be running a workshop at DSA in Kenya from June 2-5th 2024. Please note that we are also accepting (and scoring) entries, and there are two deadlines coming up - April 8th to submit a preliminary entry to the Challenge and April 15th to submit a (placeholder) abstract to CinC.

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Duke Critical Care Datathon: 13-14 April 2024

Feb. 7, 2024

Our colleagues at Duke are hosting a Critical Care Datathon on April 13-14, 2024. The Datathon is a collaborative two-day event that connects critical care clinicians with data scientists to develop pragmatic data-driven models using de-identified critical care electronic health record datasets.

Using de-identified critical care electronic health record datasets (including MIMIC and the eICU Collaborative Research Database), participants will develop new projects in 36 hours, from problem to abstract (and more)! 

Participants will be organized into teams that are half-data science, half-clinical. You do not need to have a team; the organizers will help you find a team. Questions will be crowdsourced. No experience is required.

  • If you are a clinician, your interest, but not expertise, in data science is required. 
  • If you are a data scientist, your interest, but not expertise, in healthcare and critical care is required. 

For more information, see:

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CHIL 2024: Submit your paper by Friday, 16 February

Feb. 6, 2024

The 2024 Conference on Health, Inference, and Learning (CHIL) invites submissions focused on artificial intelligence and machine learning (AI/ML) techniques that address challenges in health, which includes clinical healthcare, public health, health economics, informatics, and more. For full details, refer to the online Call for Papers: 

This year, CHIL 2024 will accept submissions for three distinct tracks: Models and MethodsApplications and Practice, and Policy, Impact and Society. Accepted papers will be published in the Proceedings of Machine Learning Research (PMLR). We are also offering Best Paper Awards to recognize outstanding work across all tracks.

The deadline for submissions has been extended to: Friday, 16 Feb 2024 at 11:59pm AoE. Submit your paper at:


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Conference on Health, Inference, and Learning (CHIL): Submit your paper by Mon 5 Feb, 2024!

Jan. 30, 2024

The 2024 Conference on Health, Inference, and Learning (CHIL) invites submissions focused on artificial intelligence and machine learning (AI/ML) techniques that address challenges in health, which includes clinical healthcare, public health, health economics, informatics, and more. For full details, refer to the online Call for Papers: 

This year, CHIL 2024 will accept submissions for three distinct tracks: Models and MethodsApplications and Practice, and Policy, Impact and Society. Accepted papers will be published in the Proceedings of Machine Learning Research (PMLR). We are also offering Best Paper Awards to recognize outstanding work across all tracks.

Submissions are due on February 5th, 11:59 PM EST in the form of anonymized PDF files. All submissions for CHIL 2024 will be managed through the OpenReview system. Similar to last year, we have a full author response period and reviewer discussion period to ensure proper feedback on the work. 

Hosted by The Association of Health, Learning, and Inference (AHLI), the CHIL conferences have consistently served as premier scientific meetings, uniting clinicians and researchers from both industry and academia, and weaving a rich tapestry of knowledge and innovation.

Building on a series of conferences and events since 2019, CHIL has persistently set a benchmark in interdisciplinary research within the realms of machine learning and health, demonstrated through its impactful sessions (2020202120222023). Following the resounding success of CHIL 2023 at the Broad Institute, Cambridge, we are thrilled to announce that CHIL 2024 will continue fostering insightful discussions and collaborations in the field. The 5th annual conference will take place in-person from June 27-28 at the Verizon Executive Education Center at Cornell Tech in New York City. 

Important Dates

  • Submissions due: Feb 5, 2024 at 11:59pm
  • Bidding opens for reviewers: Feb 6, 2024 at 11:59pm
  • Reviews released: Mar 4, 2024 by 11:59pm
  • Author/Reviewer discussion period: Mar 10-21, 2024
  • Author notification: Apr 3, 2024 by 11:59pm
  • CHIL conference: June 27-28, 2024

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George B. Moody PhysioNet Challenge 2024: Challenge Opening

Jan. 26, 2024

We are delighted to announce the opening of the George B. Moody PhysioNet Challenge 2024. The 2024 Challenge invites teams to develop algorithms for digitizing and classifying electrocardiograms (ECGs) captured from images or paper printouts.

Despite recent advances in digital ECG devices, paper or physical ECGs remain common, especially in the Global South. These paper ECGs document the history and diversity of cardiovascular diseases (CVDs), and algorithms that can digitize and classify these images have the potential to improve our understanding and treatment of CVDs, especially for underrepresented and underserved populations.

We have shared example code and scoring code in both MATLAB and Python and synthetic ECG generation code in Python. While last year’s Challenge had the largest dataset yet, this year’s Challenge begins with a much more tractable dataset that you may already have on your machine, and you can use the provided code to create ECG images with realistic artifacts. We will also augment these data to create a much richer and more representative dataset, so stay tuned for more announcements. We will open the scoring system in the coming days.

See the Challenge website for more information, rules and deadlines:

As in previous years, we have divided the Challenge into two phases: an unofficial phase and an official phase. The unofficial phase solicits feedback from the research community (i.e., you) to help us to improve the Challenge for the official phase, so we require teams to register and participate in the unofficial phase of the Challenge to be eligible for a prize. Please enter early and often – we need you to look for quirks in our data, our scoring system, and otherwise. We are imperfect (and bandwidth-limited), so please send us suggestions via the forum (see below). We rely on the community to help us to improve the quality of the Challenge each year.

More information will be posted on the PhysioNet Challenge website and the Challenge forum as it becomes available. Please post questions and comments to the Challenge forum as well. However, if your question reveals information about your entry, then please email info [at] instead to help us safeguard the diversity of approaches to the Challenge. We may post parts of our replies publicly if we feel that all Challengers should benefit from the information contained in our responses. We will not answer emails about the Challenge sent to other email addresses.

Many thanks again for your continued support of this event, and we hope that you enjoy the 2024 Challenge!

Call for Papers on Computational Tools for Physiological Time Series Analysis

Jan. 22, 2024

On behalf of our colleagues, we are pleased to announce a call for papers for a focus collection in IOP Physiological Measurement on the topic of "Open Source and Validated Computational Tools for Physiological Time Series Analysis".

Physiological time series analysis plays a crucial role in understanding the complex dynamics of biological systems and their response to stimuli and interventions. The availability of reliable, open-source computational tools is essential for advancing research in this field, facilitating reproducibility, promoting collaboration, and accelerating scientific discoveries.

This focus collection aims to showcase the latest advancements in open-source tools and methodologies that have been rigorously validated for the analysis of physiological time series data.

Guest Editors

  • Joachim A. Behar, Technion Institute of Technology, Israel
  • Peter H. Charlton, University of Cambridge, UK
  • Márton Áron Goda, Technion Institute of Technology, Israel
  • Maarten De Vos, KU Leuven, Belgium

For questions, please contact Dr. Joachim A. Behar (

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Announcing the SNOMED CT Entity Linking Challenge

News from: SNOMED CT Entity Linking Challenge v1.0.0.

Dec. 20, 2023

We are pleased to announce the launch of the SNOMED CT Entity Linking Challenge in collaboration with SNOMED International, Veratai, and DrivenData. Sponsored by SNOMED International, the challenge seeks to advance the development of Entity Linking models that operate on unstructured clinical text. 

Participants are tasked with developing a model to annotate MIMIC-IV-Note discharge summaries with SNOMED CT concepts. Training data, comprising ~300 annotated discharge summaries, has been made available on PhysioNet at

Sign up now at!

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PhD opportunities at the European INSIDE-HEART consortium (deadline for applications: 31 Jan 2024)

Dec. 11, 2023

INSIDE-HEART brings together universities, companies and hospitals from Italy, Finland, France, Israel, Netherlands, Spain, and Sweden to establish a multi-disciplinary network to tackle the design and early-phase validation of digital biomarkers targeting the diagnosis of supraventricular arrhythmias (SVAs) and their associated potential for adverse risk assessment.

Our colleagues in the network are looking for 10 motivated PhD candidates, funded by the European Union’s Horizon Europe program under the Marie Skłodowska Curie Actions. For further information and details on how to apply, see: The call for applications is open until 31 January 2024.

The INSIDE-HEART project is coordinated by the Politecnico di Milano. Please direct questions to

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DARPA Triage Challenge: Qualification extended through Nov 27

Nov. 6, 2023

Qualification for the DARPA Triage Challenge has been extended through November 27, 2023 at 23:59. We encourage you to join the challenge as a self-funded team for the Systems, Virtual and Data Competitions. You may compete in one or more challenge tracks, where qualification must be entered for each track individually. 

To register, please visit the Team Qualification Portal at:

For more information on the challenge, see: or contact

Join the DARPA Triage Challenge! Deadline for registration: Monday 13 November, 2023

Oct. 18, 2023

The Defense Advanced Research Projects Agency (DARPA), a research and development agency within the Department of Defense, is seeking competitors for a new medical response challenge. The DARPA Triage Challenge aims to drive breakthrough innovations that improve medical response time during mass casualty incidents in complex military and civilian settings, especially when medical resources are limited relative to the need.

The challenge includes a series of technical challenge events to drive breakthrough innovations in the identification of physiological features (signatures) of injury, and help medical responders perform scalable, timely, and accurate triage. The challenge has two primary triage competitions – Systems and Virtual – and a secondary triage Data competition. The Systems and Virtual competitions focus on stand-off sensing of physiological data using autonomous platforms – uncrewed aerial and ground vehicles – during primary triage. Competitors will conduct real-time sensor data analysis to identify casualties for urgent hands-on evaluation by medical personnel.

Relevant to the PhysioNet community, the Data competition seeks to identify physiological signatures of injury derived from data captured by non-invasive sensors (contact-based or stand-off). Such advances could accelerate responders’ anticipatory decisions and prioritization for medical care during secondary triage. Competitors will attempt to develop algorithms that detect signatures in these data streams to provide decision support appropriate for austere and complex pre-hospital settings. Of particular interest are early signatures indicating a need for life-saving interventions against conditions that medics are trained and equipped to treat during secondary triage, such as hemorrhage and airway injuries.

The Data competition will use DARPA-provided de-identified, multi-modal physiological data from trauma patients across diverse settings and cohorts provided by the DARPA Research Infrastructure for Trauma with Medical Observations effort. Data types include, but are not limited, to: photoplethysmography (PPG) waveforms, medical procedures, imaging results and video footage during prehospital helicopter transport and in the trauma bay.

Prizes for year one:

  • Systems Competition: Up to $200K Prize pool
  • Virtual Competition: Up to $100K Prize pool
  • Data Competition: Up to $200K Prize pool

Total Prizes $7M over three challenges

DARPA is currently seeking self-funded competitors. Join us by registering on the Qualification Portal, now through Nov. 13, 2023.

For more information visit the DARPA Triage Challenge website.

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Call for partners interested in synthetic patient data

Sept. 27, 2023

The Google Research team is looking for partners to understand the needs and requirements for synthetic data. They have capabilities to generate both structured and unstructured patient data as well as images for infrastructure testing and medical research. Please contact us if you are interested in the partnership.

MIMIC-IV-ECG module released

News from: MIMIC-IV-ECG: Diagnostic Electrocardiogram Matched Subset v1.0.

Sept. 15, 2023

The MIMIC-IV-ECG module is now available. This module contains approximately 800,000 diagnostic electrocardiograms across nearly 160,000 unique patients. The vast majority of ECGs for patients who appear in the MIMIC-IV Clinical Database are included. The patients in MIMIC-IV-ECG have been matched against the MIMIC-IV Clinical Database, making it possible to link to information across the MIMIC-IV modules. When a cardiologist report is available for a given ECG, we provide information for linking to it.

FFA-IR dataset is unavailable until further notice

News from: FFA-IR: Towards an Explainable and Reliable Medical Report Generation Benchmark v1.0.0.

Sept. 6, 2023

The authors of the FFA-IR dataset have asked for downloads to be disabled until further notice to adhere with local policy changes. We apologize for the inconvenience and hope to make the files available again in the future.

I-CARE is now available on Google Cloud

News from: I-CARE: International Cardiac Arrest REsearch consortium Database v2.0.

June 22, 2023

I-CARE v.2.0 is now available on Google Cloud. For details on downloading the dataset or working with it directly in the cloud, see the Files section of the project description.

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Announcing CXR-LT, a competition for long-tailed disease classification on chest X-rays

News from: CXR-LT: Multi-Label Long-Tailed Classification on Chest X-Rays v1.0.0.

June 21, 2023

We are pleased to announce CXR-LT, a competition on Multi-Label Long-Tailed Classification on Chest X-Rays. Many real-world problems, including diagnostic medical imaging exams, are “long-tailed”: there are a few common findings followed by more relatively rare conditions. This competition will provide a challenging large-scale multi-label long-tailed learning task on chest X-rays (CXRs), encouraging community engagement with this emerging interdisciplinary topic.

CXR-LT is organized as a shared task for the workshop on Computer Vision for Automated Medical Diagnosis (CVAMD) held in association with the International Conference on Computer Vision (ICCV) 2023. Participants will be invited to submit their solutions for publication presentation at CVAMD 2023 and publication in the ICCV 2023 workshop proceedings.

The challenge uses an expanded version of MIMIC-CXR-JPG v2.0.0, a large benchmark dataset for automated thorax disease classification. Each CXR study in the dataset was labeled with 12 newly added disease findings extracted from the associated radiology reports. The resulting long-tailed (LT) dataset contains 377,110 CXRs, each labeled with at least one of 26 clinical findings (including a "No Finding" class).

Important dates

05/01/2023: Development Phase begins. Participants can begin making submissions and tracking results on the public leaderboard.
07/14/2023: Testing Phase begins. Unlabeled test data will be released to registered participants. The leaderboard will be kept private for this phase.
07/17/2023: Competition ends. Participants are invited to submit their solutions as 8-page papers to ICCV CVAMD 2023!
07/28/2023: ICCV CVAMD 2023 submission deadline. (Competition participants may receive an extension if needed.)
08/11/2023: ICCV CVAMD 2023 acceptance notification.
10/06/2023: ICCV CVAMD 2023 workshop.

This competition is supported in part by the Artificial Intelligence Journal (AIJ). For any questions, please contact

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I-CARE will shortly be available on Google Cloud

June 20, 2023

We are aware that downloading the I-CARE dataset from PhysioNet is currently slow and we apologize for the inconvenience. To resolve this issue, we are currently transferring the dataset to Google Cloud. Once the transfer is complete, the dataset can be analyzed directly in the cloud or downloaded using Google Cloud Utilities. Please check here for updates.