An interesting review of KDD and MUCMD (Meaningful Use of Complex Medical Data) 2011:
At KDD I enjoyed Stephen Boyd’s invited talk about optimization quite a bit. However, the most interesting talk for me was David Haussler’s. His talk started out with a formidable load of biological complexity. About half-way through you start wondering, “can this be used to help with cancer?” And at the end he connects it directly to use with a call to arms for the audience: cure cancer. The core thesis here is that cancer is a complex set of diseases which can be distentangled via genetic assays, allowing attacking the specific signature of individual cancers. However, the data quantity and complex dependencies within the data require systematic and relatively automatic prediction and analysis algorithms of the kind that we are best familiar with.
Cites a number their favorite papers. Which ones are yours?