WiDS Datathon 2020
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Congratulations to the WiDS Datathon winners, announced at WiDS Stanford on March 2nd. These three teams were at the top of a very active leaderboard, with 951 teams submitting 12,644 entries. We also want to thank all WiDS 2020 ambassadors who hosted WiDS Datathon workshops, across the globe. You can read more about this year's datathon competition below. Subscribe to the WiDS Datathon mailing list to be notified of datathon updates.
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What is a Datathon?A datathon is a data-focused hackathon — given a dataset and a limited amount of time, participants are challenged to use their creativity and data science skills to build, test, and explore solutions. Try something new, apply what you know, learn from other participants, and improve your data science skills along the way!
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WiDS Datathon Webinar: Lessons Learned + Best Practices with Health Data
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This open-to-all webinar on-demand features distinguished panelists that explore the challenges and opportunities of working with healthcare data, and discusses issues around the technology and the clinical aspect of healthcare machine learning. Webinar slides
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Excellence in Research Award
To help encourage deeper exploration and the development of collaborative data science innovations, we are hosting a second phase of the WiDS Datathon this year — with a new WiDS Datathon Excellence in Research Award. We invite you to share more details about your work with WiDS Datathon 2020 data through a one-page research paper.
Background: This Year's Dataset and Challenge
This year's WiDS Datathon focused 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. The WiDS Datathon was hosted on Kaggle, an online community of data scientists and machine learners.
The challenge was to create a model that uses data from the first 24 hours of intensive care to predict patient survival. MIT's GOSSIS community initiative, with privacy certification from the Harvard Privacy Lab, has provided a dataset of more than 130,000 hospital Intensive Care Unit (ICU) visits from patients, spanning a one-year timeframe. This data is part of a growing global effort and consortium spanning Argentina, Australia, New Zealand, Sri Lanka, Brazil, and more than 200 hospitals in the United States.
The challenge was to create a model that uses data from the first 24 hours of intensive care to predict patient survival. MIT's GOSSIS community initiative, with privacy certification from the Harvard Privacy Lab, has provided a dataset of more than 130,000 hospital Intensive Care Unit (ICU) visits from patients, spanning a one-year timeframe. This data is part of a growing global effort and consortium spanning Argentina, Australia, New Zealand, Sri Lanka, Brazil, and more than 200 hospitals in the United States.
Who Can Participate in the Datathon
Photo credit: Dana J. Quigley
We invite anyone, from those new to data science to veterans of the field, to participate. For those who have never tried machine learning or worked with health data before, we published a listing of resources and tutorials.
The WiDS Datathon aims to inspire women worldwide to learn more about data science, and to create a supportive environment for women to connect with others in their community who share their interests. Toward these ends, we open the datathon to individuals or teams of up to 4; at least half of each team must be women (individuals identifying as female participants).
Participants included students, faculty, and individuals with various roles in non-profit, academic, government, and industry organizations.
The WiDS Datathon aims to inspire women worldwide to learn more about data science, and to create a supportive environment for women to connect with others in their community who share their interests. Toward these ends, we open the datathon to individuals or teams of up to 4; at least half of each team must be women (individuals identifying as female participants).
Participants included students, faculty, and individuals with various roles in non-profit, academic, government, and industry organizations.
The WiDS Datathon is a collaboration led by the Global WiDS team at Stanford, the West Big Data Innovation Hub, and the WiDS Datathon committee:
The WiDS Datathon is made possible by the following
WiDS Global Visionary Sponsors:
