Stanford ICME Announces WiDS Datathon to Predict ICU Mortality

Global Competition Encourages Women to Advance Data Science Skills

STANFORD, Calif.–(BUSINESS WIRE)–The Women in Data Science (WiDS) initiative today announced that its 2020 datathon will focus on Intensive Care Unit (ICU) data to help predict patient mortality. The WiDS datathon is part of the WiDS global initiative, which reaches more than 100,000 people worldwide each year through a technical conference at Stanford and at 150+ locations around the world, plus online through live streaming and a podcast series. WiDS is part of the Stanford Institute for Computational and Mathematical Engineering (ICME) and aims to inspire and educate data scientists worldwide, regardless of gender, and to support women in the field. ​

“WiDS brings together some of the best and most creative data scientists in the world,” said Karen Matthys, Stanford ICME Executive Director, External Partners, and Co-Director of the WiDS Conference. “This year the datathon participants are seeking patterns and insights in data to find ways to reduce ICU deaths. There are approximately 500,000 ICU deaths annually in the U.S. alone. Our data scientists will race each other and the clock to find insights for addressing ICU mortality.”

The WiDS datathon encourages women to hone their data-science skills through a predictive analytics challenge focused on social impact. The WiDS datathon participants receive access to an ICU mortality dataset on Kaggle, the leading platform for data science competitions, and can compare the accuracy of their models through a public leaderboard. The WiDS datathon greatly increases the percentage of women participating in a Kaggle competition from less than 20 percent for normal competitions to 50 percent for the WiDS competition.

The WiDS datathon brings people together across borders to work in teams, solving global challenges. Participants from previous competitions came from dozens of countries across six continents, including the US, India, Sweden, the UK, Nigeria, Tanzania, and Bolivia. The datathon winners will be announced at the WiDS Conference at Stanford University on March 2, 2020.

“The WiDS datathon always focuses on topics with significant social benefit,” said Matthys. “We believe that data science and machine learning can help improve ICU care for all patients and ultimately reduce ICU deaths.”

Participation is free and open to anyone who qualifies for a Kaggle competition. Tutorials are available for people who are new to data science, and workshops will be hosted by select WiDS ambassadors worldwide. Participants can register on the WiDS datathon page where registrants can also sign up for the WiDS datathon mailing list and follow a link to create a Kaggle account.

The WiDS datathon is a collaboration led by the global WiDS team at Stanford ICME, the West Big Data Innovation Hub, and the WiDS datathon committee, and is made possible by the Global Visionary Sponsors: Facebook, Intuit, Walmart Labs, and Wells Fargo.

About WiDS

The Women in Data Science (WiDS) initiative aims to inspire and educate data scientists worldwide, regardless of gender, and to support women in the field. ​WiDS started as a conference at Stanford in November 2015. Now, WiDS includes a global conference, with approximately 150+ regional events worldwide; a datathon, encouraging participants to hone their skills using a social impact challenge; a podcast, featuring leaders in the field talking about their work, their journeys, and lessons learned; and ongoing education initiatives. ​

About the Institute for Computational & Mathematical Engineering (ICME) at Stanford University

ICME is a home at Stanford for an increasingly critical multidisciplinary field that uses advanced mathematical and computing capabilities to understand and solve big, complex problems. ICME provides a degree-granting program for MS and PhD students who apply their studies to a wide range of domains, supported by more than 50 affiliated faculty from 20+ departments across the university.


Forrest Carman

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