From Safari to the Stratified Medicine: How Machine Learning Connects the Dots to Create a Future Health Trajectory

Several years ago, I set out with my family on an African Safari adventure, engaging a professional animal tracker to lead us to see all sorts of wildlife – lion, elephants, rhinoceros, giraffes, and more. We were all amazed by the tracker’s ability to describe animal activity and lead us to some of these animals simply by interpreting small pieces of information from the surrounding area and skillfully piecing them together. The trajectory of a simple footprint, a broken branch, or even a scratch on a tree enabled the tracker to lead us to wonderful discoveries. As a health technology executive, I recognized a clear parallel between the work of the professional animal tracker and the use of machine learning in healthcare.  Both share the ability to harmonize data to tell a potentially meaningful story. Trackers are trained to connect the dots between small, scattered pieces of information to reach a probability of an animal being in a specific location at a certain time. Through both experience and inherited learning, they know how to identify and connect the dots. Just as they pick up hints and relay insights which, to the average person, may be imperceptible or seem insignificant by themselves, so does machine learning.