Nearly all aspects of modern life are in some way being changed by big data and machine learning. Netflix knows what movies people like to watch and Google knows what people want to know based on their search histories. Indeed, Google has recently begun to replace much of its existing non–machine learning technology with machine learning algorithms, and there is great optimism that these techniques can provide similar improvements across many sectors.
It is no surprise then that medicine is awash with claims of revolution from the application of machine learning to big healthcare data. Recent examples have demonstrated that big data and machine learning can create algorithms that perform on par with human physicians.1 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. It is our hope that elucidating these connections will demystify these techniques and provide a set of reasonable expectations for the role of machine learning and big data in healthcare.
Machine learning was originally described as a program that learns to perform a task or make a decision automatically from data, rather than having the behavior explicitly programmed. However, this definition is very broad and could cover nearly any form of data-driven approach. For instance, consider the Framingham cardiovascular risk score, which assigns points to various factors and produces a number that predicts 10-year cardiovascular risk. Should this be considered an example of machine learning? The answer might obviously seem to be no. Closer inspection of the Framingham risk score reveals that the answer might not be as obvious as it first seems. The score was originally created2 by fitting a proportional hazards model to data from more than 5300 patients, and so the “rule” was in fact learned entirely from data. Designating a risk score as a machine learning algorithm might seem a strange notion, but this example reveals the uncertain nature of the original definition of machine learning.There is no doubt that 'machine learning', artificial intelligence will gradually intrude upon our routines almost unnoticed, just as chatbots already have done so.
Big Data and Machine Learning in Health Care | Clinical Decision Support | JAMA | JAMA Network