A recent article in the Journal of the American Medical Association analyzes the role of big data and machine learning in modern health care.
The article, published March 12, was penned by Andrew Beam, PhD, and Isaac Kohane, MD, PhD.
“Though machine learning and big data may seem mysterious at first, they are in fact deeply related to traditional statistical models that are recognizable to most clinicians,” they write.
Beam and Kohane attempt to break down what defines machine learning, and how professional involvement on behalf of humans defines where certain process land on a machine learning spectrum.
The authors use as an example the Framingham cardiovascular risk score, which uses a number of variables to produce a number which predicts cardiovascular risk over 10 years.