Lung cancer is one of the most common types of cancer, with nearly 225,000 new cases of the disease expected in the U.S. in 2016. Using a data set of high-resolution scans of lungs provided by the National Cancer Institute, participants will develop artificial intelligence algorithms to accurately determine when lesions in the lungs are cancerous. This will dramatically reduce the false positive rate that prevents low-dose CT scans from being widely used for lung cancer detection. Competition results have the potential to advance our understanding of how all types of cancer develop and spread in the body. They'll also free radiologists to spend more time with patients.

In the U.S., cancer will strike two in every five people in their lifetimes. But it affects all of us. That's why, in 2015, the office of the Vice President announced the Cancer Moonshot. It's an audacious effort to make a decade's worth of progress in cancer prevention, diagnosis, and treatment in just five years. Beginning today, the 2017 Data Science Bowl will pursue one of the Cancer Moonshot's key goals: unleashing the power of data against this deadly disease. Presented by Booz Allen and Kaggle, the competition will convene the data science and medical communities to develop cancer detection algorithms, and help end the disease as we know it.