Booz Allen and Kaggle Call on Global Data Science Community to Change the Future of Heart Health

Booz Allen and Kaggle Call on Global Data Science Community to Change the Future of Heart Health

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.@BoozAllen & @Kaggle Launch #DataSciBowl competition to power future of #heart #health
Monday, December 14, 2015 - 12:35pm

CONTENT: Article

Each year, cardiovascular disease causes more than 30 percent of deaths around the globe. In the United States, someone is diagnosed with the condition once every 43 seconds. Finding a way to enhance and expedite the diagnosis of heart disease requires the attention and support of public and private sector organizations worldwide. Booz Allen Hamilton (NYSE: BAH) and Kaggle today announced that the second annual Data Science Bowl will call on the global data science community to create a set of steps, or algorithms, to help transform diagnosis of heart disease.

Through a partnership with the National Institutes of Health (NIH), participants in the 90-day competition will be given MRI images and asked to develop an algorithm to automate the measurements that are key indicators of heart disease.

Roman Salasznyk, Ph.D., Senior Associate, Regulatory Science Practice of Booz Allen Hamilton comments on the effort launched today:

At the Heart of Data Science

Every 24 hours, your heart beats approximately 100,000 times. No matter whether it was a day of triumph or defeat, discovery or pursuit, love or loss, you can count on relatively 100,000 reminders that you have embarked, once again, upon another chapter of the best story ever told – yours. In a year, that remarkable force will take 2.5 billion steps toward the future. So, though our hearts may, at times, yearn for the past or a present that never was, its beating drives us ever forward. And that is a journey that must be protected at all costs.   

Today, Booz Allen Hamilton and Kaggle are asking the global data science community to do what it does best – roll up its sleeves, get to work and help to solve a major, international challenge through the power of analytics. To that end, the second annual Data Science Bowl will ask participants over the next 90 days to create a set of algorithms – or problem-solving processes – that will help the National Institutes of Health and healthcare professionals automate measurements, which are key indicators of heart disease – the cause of more than 30 percent of deaths around the world. In essence, we are asking data scientists everywhere to use their skills to help people live longer, healthier lives. And, as you can probably imagine, we’re beyond excited for you to get started.

The heart’s ability to efficiently pump blood is currently measured through a manual process that takes a specially trained cardiologist approximately 20 minutes to complete – vital time the physician could be spending with his or her patients. The Data Science Bowl’s data set features more than 1,000 images from a broad spectrum of individuals with different ages and genders, ensuring the winning algorithm will be able to handle the varying, yet precise demands of real-world patient-care while drastically cutting the time and cost of the traditional process.

We are trying to change heart health research in 90 days, which is admittedly no small order. If you’re going to transform the world, though, you may as well start the clock today. And, at the end of 90 days, the participants who deliver the most accurate algorithm will not only have the honor of redefining heart health research, but will also be granted $125,000, with the second and third-place teams receiving $50,000 and $25,000, respectively.

We hope our competitors will test their skills, discover an answer to the previously impossible, and have an unforgettable experience in the pursuit of both. But, above all, we hope this competition demonstrates to the world that data science has the ability to uncover truths in our beautiful and complex planet, which examine the past and present to change the future – and ourselves – forever.

We hope you will join us. To learn more, visit: