Nearly 10,000 Global Problem Solvers Yield Winning Formulas to Improve Detection of Lung Cancer in Third Annual Data Science Bowl

Booz Allen Hamilton and Kaggle competition nets nearly 18,000 algorithms aimed at unlocking the lifesaving potential of cancer screening

Summary:

  • The National Cancer Institute will work on winning solutions closely with the scientific community and other stakeholders to advance low dose CT lung cancer screening
  • Winners will split a prize purse of $1 million, the largest-ever for the competition, funded by the Laura and John Arnold Foundation

In the 2017 Data Science Bowl, competitors used anonymized, high-resolution lung scans from hundreds of patients provided by the National Cancer Institute (NCI), to create algorithms that can improve lung cancer screening technology. The participants created algorithms that can accurately determine when lesions in the lungs are cancerous and thereby dramatically decreasing the false positive rate of current low-dose CT technology. (Graphic: Data Science Bowl)

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MCLEAN, Va.--()--Booz Allen Hamilton (NYSE: BAH) and Kaggle today announced the winners of the third annual Data Science Bowl, a competition that harnesses the power of data science and crowdsourcing to tackle some of the world’s toughest problems. This year’s challenge brought together nearly 10,000 participants from across the world. Collectively they spent more than an estimated 150,000 hours and submitted nearly 18,000 algorithms—all aiming to help medical professionals detect lung cancer earlier and with better accuracy.

2017 Data Science Bowl winners include:

  • First Place: Liao Fangzhou and Zhe Li, two researchers from China’s Tsinghua University who have no formal medical background but were able to apply their analytics skills to an unfamiliar but challenging area of research.
  • Second Place: Julian de Wit and Daniel Hammack, both software and machine learning engineers based in the Netherlands. Julian came in third in the Data Science Bowl 2016.
  • Third Place: Team Aidence, members of which work for a Netherlands-based company that applies deep learning to medical image interpretation.

Josh Sullivan, senior vice president at Booz Allen, said, “The Data Science Bowl shows that the power of collective ingenuity, data science and advanced analytics can be harnessed to tackle society’s toughest challenges like eradicating cancer. This year’s complex problem—improving the accuracy of lung cancer screening—required the diversity of perspectives and approaches that only a crowd-sourced challenge like the Data Science Bowl can provide. We look forward to advancing these solutions and in the fight against cancer.”

Lung cancer is the most common type of cancer worldwide, affecting nearly 225,000 people each year in the United States alone. Low-dose computed tomography (CT) is a breakthrough technology for early detection, with the potential to reduce lung cancer deaths by 20 percent. But, the technology must overcome a relatively high false positive rate.

Using anonymized high-resolution lung scans in one of the largest data sets to be made publicly available, provided by the National Cancer Institute (NCI), participants created algorithms that can improve lung cancer screening technology. The participants created algorithms that can accurately determine when lesions in the lungs are cancerous and dramatically decrease the false positive rate of current low-dose CT technology.

“This is one of the most important competitions Kaggle has ever hosted,” said Anthony Goldbloom, CEO, Kaggle. “Recent breakthroughs in deep neural networks may make it feasible to diagnose lung cancer from CT scans with higher accuracy than previously possible. The interest in this year’s Data Science Bowl has been unprecedented for a competition of this size. The results are incredibly promising.”

Top teams will present their winning solutions next week at the 2017 GPU Technology Conference in San Jose, California, hosted by NVIDIA, a Data Science Bowl sponsor.

“Reducing the false positive rate of low-dose CT scans is a critical step in improving the accuracy of CT screening of lung cancer and having a positive impact on public health,” said Keyvan Farahani, Program Director, National Cancer Institute, who provided scientific guidance regarding the competition’s design and datasets. “NCI is committed to working closely with the scientific community, the Food and Drug Administration, and other stakeholders to utilize this year’s top-ranking solutions to further advance the field of lung cancer screening.”

For more information, including past winners, please visit www.datasciencebowl.com.

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About Booz Allen Hamilton

Booz Allen Hamilton (NYSE: BAH) has been at the forefront of strategy and technology for more than 100 years. Today, the firm provides management and technology consulting and engineering services to leading Fortune 500 corporations, governments, and not-for-profits across the globe. Booz Allen partners with public and private sector clients to solve their most difficult challenges through a combination of consulting, analytics, mission operations, technology, systems delivery, cybersecurity, engineering, and innovation expertise.

With international headquarters in McLean, Virginia, the firm employs approximately 23,000 people globally, and had revenue of $5.41 billion for the 12 months ended March 31, 2016. To learn more, visit BoozAllen.com.

About Kaggle

Kaggle is the world's largest online data science competition community. with more than 950,000 members across 194 countries, the Kaggle community uses its diverse set of academic backgrounds to solve complex data science problems. Working as individuals or in teams, the winning competitors are awarded prizes and industry recognition for their accomplishments. The top competitors are invited to work on the most interesting and sensitive business problems from some of the world’s biggest companies through Masters Competitions.

Contacts

Booz Allen Hamilton
Joseph Campbell, 703-377-4422
Campbell_Joseph@bah.com

Release Summary

Nearly 10,000 global data scientists, problem solvers competed to find winning formulas to improve detection of lung cancer in 3rd annual Data Science Bowl.

Contacts

Booz Allen Hamilton
Joseph Campbell, 703-377-4422
Campbell_Joseph@bah.com