Background on the challenge Getting a rapid understanding of the context of a patient’s overall health has been particularly important during the COVID-19 pandemic as healthcare workers around the world struggle with hospitals overloaded by patients in critical condition. ICUs often lack verified medical histories for incoming patients. A patient in distress or a patient who is brought in confused or unresponsive may not be able to provide information about chronic conditions such as heart disease, injuries, or diabetes. Medical records may take days to transfer, especially for a patient from another medical provider or system. Knowledge about chronic conditions can inform clinical decisions about patient care and ultimately improve patient outcomes. During November’s American Diabetes Month various groups raised awareness about this disease that afflicts 34.2 million Americans or 10.5% of the population. And one in five people (7.3 million) who met the laboratory criteria for it aren’t aware they are living with the disease or how to manage it. People with diabetes are also at risk for more serious outcomes from COVID-19. Between February and May, a CDC study that analyzed 10,000 deaths found that 40 percent of those who have died from COVID-19 were living with diabetes. On a global scale, 463 million adults were living with diabetes in 2019, and 1 in 2 (232 million) people were undiagnosed. The dataset and challenge We will take a closer look at data similar to the WiDS 2020 Datathon data from MIT’s GOSSIS (Global Open Source Severity of Illness Score) Initiative, but instead of predicting patient survival, this year the WiDS Datathon will focus on creating models to classify whether patients have been diagnosed with a certain type of diabetes which could inform treatment in the ICU. Who can participate in the datathon We invite anyone from those new to data science to veterans of the field to participate. For those who have never tried machine learning, we will be releasing a series of guides to help you get started with the algorithms and dataset. 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 (people identifying as female). Participants can be students, faculty, government workers, members of NGOs, or industry members. How it works The datathon will run from early January-February 2021 on Kaggle, an online community of data scientists. Labeled training and validation sets will be provided for model development; you will then upload your classifications for an unlabeled test set to Kaggle and these will be used to determine the public leaderboard rankings and the winners of the competition. Winners will be announced at the WiDS Worldwide Conference held virtually on March 8, 2021. Beyond the leaderboard rankings, individuals and teams will also have an opportunity to submit papers about their work to be eligible for an Excellence in Research Award from the National Science Foundation Big Data Innovation Hubs. Getting started Make your plans to build a team, hone your data science skills, and join us in this year’s challenge focused on social impact. We recommend you:
Lastly, be creative, and have fun! Good luck to all participants — we’re so excited to see what you create.  Comments are closed.
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