TR personalized medicine briefing
MIT’s Technology Review magazine has a briefing on personalized medicine. It’s worth a look, although it’s quite heavily tilted towards DNA sequencing technology (which I am interested in, but there is a lot more to personalized medicine). Not surprisingly, one of the articles in the briefing makes the point that the biggest bottleneck in personalized medicine will be data analysis, the risk being that “…we will end up with a collection of data … unable to predict anything.” (As an aside, I would be moderately wealthy if I had a euro for each time I’d read the phrase “drowning in data”, which appears in the article heading. I think I even rejected that as a name for this blog. It would be nice to see someone come up with a fresh alternative verb to “drowning” …)
Technology Review also has a piece on how IBM has started to put their mathematicians to work in business analytics. They mention a neat technique I hadn’t been aware of: “…they used a technique called high-quantile modeling–which tries to predict, say, the 90th percentile of a distribution rather than the mean–to estimate potential spending by each customer and calculate how much of that demand IBM could fulfill“.
The last part of the article talks about a very interesting problem: how to model a system where output from the model itself affects the system, or as the article puts it “…situations where a model must incorporate behavioral changes that the model itself has inspired“. I’m surprised the article doesn’t mention the obvious applicability of this to the stock market, where of course thousands of professional and amateur data miners use prediction models (their own and others’) to determine how they buy and sell stocks. Instead, its example comes from traffic control:
For example, […] a traffic congestion system might use messages sent to GPS units to direct drivers away from the site of a highway accident. But the model would also have to calculate how many people would take its advice, lest it end up creating a new traffic jam on an alternate route.