|Image from KDnuggets.com|
The latest and grandest is the ongoing $3 million prize contest by Hereitage Provider Network, which opened in 2010 and lasts 2 years. The contest's stated goal is to create "an algorithm that predicts how many days a patient will spend in a hospital in the next year". Participants get a dataset of de-identified medical records of 100,000 individuals, on which they can train their algorithms. The article in KDNuggets.com suggests that this competition's goal is "to spur development of new approaches in the analysis of health data and create new predictive algorithms."
The 2010 SAS Data Mining Shootout contest was also health-related. Unfortunately, the contest webpage is no longer available (the problem description and data were previously available here), and I couldn't find any information on the winning strategies. From an article in KDNuggets:
"analyzing the medical, demographic, and behavioral data of 50,788 individuals, some of whom had diabetes. The task was to determine the economic benefit of reducing the Body Mass Indices (BMIs) of a selected number of individuals by 10% and to determine the cost savings that would accrue to the Federal Government's Medicare and Medicaid programs, as well as to the economy as a whole"In 2009, the INFORMS data mining contest was co-organized by IBM Research and Health Care Intelligence, focused on "health care quality". Strangely enough, this contest website is also gone. A brief description by the organizer (Claudia Perlich) is given on KDNuggets.com, stating the two goals :
- modeling of a patient transfer guideline for patients with a severe medical condition from a community hospital setting to tertiary hospital provider and
- assessment of the severity/risk of death of a patient's condition.
What about presentations/reports from the winners? I had a hard time finding any (here is a deck of slides by a group competing in the 2011 SAS Shootout, also health-related). But photos holding awards and checks abound.
If these health-related data mining competitions are to promote research and solutions in these fields, the contest webpages with problem description, data, as well as presentations/reports by the winners should continue to be publicly available (as for the annual KDD Cup competitions by the ACM). Posting only names and photos of the winners makes data mining competitions look more like a consulting job where the data provider is interested in solving one particular problem for its own (financial or other) benefit. There is definitely scope for a data mining group/organization to collect all this info while it is live and post it in one central website.
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