What is the
Datathon for Diabetes?
Diabetes is a global pandemic. Characterized by chronic high blood glucose levels (hyperglycemia) due to the body’s failure to produce enough insulin, diabetes affects over 9% of the population in the US alone, and of those people, approximately 25% are undiagnosed. More alarmingly so, the International Diabetes Federation (IDF) estimates that 415 million people have diabetes today – a figure that could rise to 642 million by 2040. Can data hold the answer for reversing this trend?
This simple question is being tackled at the Datathon for Diabetes, a data crunching event hosted at ITU on November 5 - 6, 2016. The goal is for students a to spend up to 32 hours diving into vast datasets to identify trends and uncover novel findings that work towards addressing the diabetes challenge. The diabetes pandemic is an interesting challenge to tackle through data analysis as diabetes itself is to a large part a data-driven disease. Key statistics like blood glucose levels, carbohydrate consumption, and insulin injections permeate the day of patients living with diabetes and their families. Further, risk factors including age, race, pregnancy, stress, certain medications, genetics, and high cholesterol all factor into the outcomes of a person living with diabetes. The application of advanced data analysis techniques can hold the key to understanding and working towards addressing this urgent challenge.
This simple question is being tackled at the Datathon for Diabetes, a data crunching event hosted at ITU on November 5 - 6, 2016. The goal is for students a to spend up to 32 hours diving into vast datasets to identify trends and uncover novel findings that work towards addressing the diabetes challenge. The diabetes pandemic is an interesting challenge to tackle through data analysis as diabetes itself is to a large part a data-driven disease. Key statistics like blood glucose levels, carbohydrate consumption, and insulin injections permeate the day of patients living with diabetes and their families. Further, risk factors including age, race, pregnancy, stress, certain medications, genetics, and high cholesterol all factor into the outcomes of a person living with diabetes. The application of advanced data analysis techniques can hold the key to understanding and working towards addressing this urgent challenge.
Who can join?
The Datathon is open to students, including post-docs, who can register either individually, or as part of a team comprised of 2 to 4 participants. We strongly encourage you to form teams beforehand. Participants registering individually will be placed in teams when arriving at the datathon.
No experience is necessary to join, but students are expected to come with knowledge of or interest in social data, data analytics, visualization, programming, statistics, or data science. Participants are encouraged to start coming up with ideas before the datathon, based on the inspirational questions that can be found here.
No experience is necessary to join, but students are expected to come with knowledge of or interest in social data, data analytics, visualization, programming, statistics, or data science. Participants are encouraged to start coming up with ideas before the datathon, based on the inspirational questions that can be found here.
Register now!We are pleased to confirm that the registration is now open. Sign up soon because the registration is closing on Sunday, 30 October 2016!
Please follow this link to register your participation. We will follow-up with more information closer to the date of the datathon. Sign up individually or in groups between two and four, and join us on Saturday, 5 November 2016 at ITU University in Copenhagen, Denmark. Those who register individually will be sorted into groups at the datathon. Limited space is available, so sign up soon. |
Prizes
Prizes will be awarded to the members of three winning groups based on criteria that will be announced at the Datathon for Diabetes. Prizes include the Apple Watch, B&O Beoplay A2, and Celluon PicoPro: Ultra-portable Laser HD Projector.