News | Artificial Intelligence | January 16, 2017

Artificial Intelligence Will be Used to Improve Lung Cancer Screenings

Third annual Data Science Bowl calls on amateur and career data scientists to help improve cancer screening technology by lowering false-positive rates

January 16, 2017 — Management consulting firm Booz Allen Hamilton  and data analytics company Kaggle recently announced that the third annual Data Science Bowl will inspire data scientists and medical communities around the world to use artificial intelligence to improve lung cancer screening technology. This year’s Data Science Bowl aligns to the call of the Vice President’s “Cancer Moonshot”, announced in January 2016, to unleash the power of data to help end cancer as we know it. The 90-day Data Science Bowl competition will award winners with $1 million in prizes. The funds for the prize purse will be provided by the Laura and John Arnold Foundation.

“Cancer is an intensely personal disease for so many of us: it hits loved ones at home, colleagues at work and friends in our communities. Improving cancer screening and treatment is among the most important responsibilities we have in the next decade,” said Josh Sullivan, Ph.D., senior vice president, Booz Allen Hamilton. “Artificial intelligence and human ingenuity can be powerful in the fight against cancer. Through last year’s Data Science Bowl, hedge fund analysts who had no medical experience created an algorithm that can review heart MRI [magnetic resonance imaging] images on par with trained technicians, helping to better heart disease screening. This year, data scientists — professional and hobbyists alike — can make a difference in the lives of millions of people facing a cancer diagnosis.”

Low-dose computed tomography (CT) scans can reduce lung cancer deaths by 20 percent, as demonstrated in National Cancer Institute (NCI) sponsored screening trials. This reduction would save more lives each year than any cancer-screening test in history. However, there are significant challenges as low-dose CT scans have a high false-positive rate, creating patient anxiety and potentially leading to costly and unnecessary diagnostic work like invasive biopsies that put patients at risk for collapsed lungs and other complications. Reducing the false positive rate is a critical step in making these scans available to more patients.

Using a data set of anonymized high-resolution lung scans provided by the Cancer Imaging Program of the NCI, Data Science Bowl participants will develop artificial intelligence algorithms that accurately determine when lesions in the lungs are cancerous, and thereby dramatically decrease the false positive rate of current low-dose CT technology.

The competition receives additional sponsorship and support from a number of leading health and technology organizations, including the American College of Radiology, Amazon Web Services, NVIDIA and many others.

“The Data Science Bowl is an exciting opportunity for data scientists to work with unique data sets that they wouldn’t have access to unless conducting medical research,” said Anthony Goldbloom, CEO, Kaggle. “This year’s competition has an especially important goal. By reducing the false positive rate of low-dose CT scans, we can not only prevent thousands of inaccurate lung cancer diagnoses, but also save lives through critical early detection of cancer.”

For more information: www.datasciencebowl.com

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