Originally published on Wed November 21, 2012 8:31 am
<em>The Matrix</em>: Which pill do you choose?
Credit Warner Bros./Photofest
Every night for months before the presidential election, Nate Silver would fire up his computer and run simulated results for his FiveThirtyEight blog on The New York Times. He ran hundreds of these simulations, tweaking variables like "white male poodle owner" turnout. Then along came Election Day. We all went out to vote (you did vote right?) and reality became the final word, trumping whatever Nate Silver's simulated universe might, or might not, have said.
Scientists working on NASA's six-wheeled rover on Mars have a problem. But it's a good problem.
They have some exciting new results from one of the rover's instruments. On the one hand, they'd like to tell everybody what they found, but on the other, they have to wait because they want to make sure their results are not just some fluke or error in their instrument.
Originally published on Mon November 26, 2012 1:55 pm
All out of nutmeg? The same algorithms that predicts your friends on Facebook can also figure out ingredient substitutions for your pumpkin pie this Thanksgiving.
Credit Courtesy of Lada Adamic.
We've been hearing a lot recently about how algorithms can predict just about anything. They find long-lost friends on Facebook and guess which books we'll buy next on Amazon. Algorithms hit the big time this month, when New York Times blogger Nate Silver used mathematical models and statistics to correctly forecast the outcome of every state in the presidential election.
xkcd: "Another thing that is a bad problem is if you're flying toward space and the parts start to fall off your space car in the wrong order. If that happens, it means you won't go to space today, or maybe ever."
There are people (and I hear from them constantly) who think if a subject is sophisticated, like science, the language that describes it should be sophisticated, too.
If smart people say torque, ribosome, limbic, stochastic and kinase, then the rest of us should knuckle down, concentrate and figure out what those words mean. That's how we'll know when we've learned something: when we've mastered the technical words.
In this post I report, in outline, a recent publication in PLOS ONE by Margaret Eppstein, Jeffrey Horbar, Jeff Buzas and myself, Stuart Kauffman. All four of us are at the University of Vermont, with Horbar also director of the Vermont Oxford Network of over 900 hospitals. I will refer to the four co-authors as "The Vermont Group." The full paper is entitled "Searching the Clinical Fitness Landscape".
Originally published on Sat November 17, 2012 6:22 am
The march of diabetes across the nation.
Credit Stephanie d'Otreppe / NPR
When it comes to diabetes, just about everyone has heard there's an epidemic upon us.
In 2010, about 18.8 million people of all ages in the U.S. had been diagnosed with diabetes, according to the Centers for Disease Control and Prevention. Another 7 million had diabetes but hadn't been diagnosed.
How much have things changed?
Back in 1995, about 4.5 percent of adults in the U.S. had been diagnosed with diabetes. By 2010, the prevalence had zoomed to 8.2 percent.