H ours before the close of Kaggle's competition to find out why almost one-third of women in the United States are not screened for cervical cancer, the leading team has submitted the 115th iteration of its model. Forty groups around the world are competing to win US$100,000 in a challenge sponsored by biotechnology company Genentech. The models are based on analyses of a 150 gigabyte database of de-identified patient data, says computational biologist Wendy Kan, who set up the challenge and works at Kaggle in San Francisco, California, a company that runs predictive modelling and analytics competitions that allow data scientists to compete to solve complex problems. In addition to finding solutions, contestants are asked to explain their reasoning. "It's very important for us to tell a story, " Kan says. Later, on a Kaggle forum, a member of the winning team presents two of the group's hypotheses: multiple chronic diseases and mental-health issues are major factors in why some women skip screening. Another Kaggle challenge, which began in December, asked participants to transform the diagnosis of heart disease by coming up with an algorithm to examine cardiac magnetic resonance imaging (MRI) scans to see how well the heart is pumping blood-"A very difficult problem," Kan says. Entrants used a cardiac MRI data set provided by the US National Heart, Lung and Blood Institute, and 192 teams were in the running for the $200,000 prize when the competition closed. The victors were two quantitative analysts who have worked with hedge funds, but had no experience in cardiology. So far, more than 450,000 data scientists have tried their hand at Kaggle's predictivemodelling puzzles, says economist Anthony Goldbloom, founder and chief executive of the organization. The problems-many pertaining to health, but others in fields that range from criminology to search technology-are set up so that the background of entrants doesn't matter, he says. As long as they have suitable modelling skills, no particular experience or qualifications are needed. "They are all smart, highly motivated and incredibly capable, " adds Goldbloom. "The winning margin is usually very small; often the difference between first and second isn't even statistically significant. " Kaggle is one of a number of organizations running open global challenges in life sciences to address knotty problems in basic biology, clinical research or health care. The approach is steadily gaining backers in academic laboratories and classrooms, drug companies and government agencies as a way to bring well-defined, but thorny problems to the attention of brilliant minds around the world. The design of the competitions varies from challenge to challenge and host to host. Some ask for modelling algorithms, others for ideas, and still more for prototype medical solutions.
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