Machine learning is a data analysis approach that automates analytical model building. Using algorithms that iterate based on the data returned to them, machine learning uses software to locate hard to discover information without being explicitly programmed on where to look. This iterative aspect of machine learning allows for independent adaptation. In other words, the computer and its software program'learns' from previous computations and the patterns that is saw to produce reliable, repeatable decisions and results. While machine learning algorithms have been around for a long time, the ability to automatically apply complex mathematical calculations to big data is now affordable enough to be applied in a variety of ways.

Artificial Intelligence is what enables any digital device to see and recognize objects, understand and reply to recognizable messages, make decisions, and even learn to change its thinking and behavior as it analyzes of data points in the distributed memory known as the cloud. IBM's Watson project is a good example of this last point especially. AI in all of these facets is already in use in the world of healthcare at a fairly basic level but what more extended role is Artificial Intelligence likely to play in healthcare in the future? Although we can't be certain about the future, we can look just a few years ahead and make several predictions upon which many experts in the healthcare technology space can agree. This includes smart individuals such as Dr. Eric Topol, Dr, Berci Meskó, and Dr. Bob Wachter, all of which have written about this. Most of the above are already starting to happen in healthcare.