Using Machine Learning with Health Data: The Challenges and Pitfalls - insideBIGDATA

Applying Machine Learning (ML) to physiological data poses several challenges. While ML can be effectively used to model well-defined systems, applying it to a system as complex as the human body dictates a much more careful approach. The bottom line is that the human body is complex and subtle, and oversimplifying – as common sense sometimes impels us to do – can be hazardous to your health" (Andrew Weil). Clinicians understand when a chronically-ill patient requires attention by monitoring vital signs, as well as hundreds of other features. The human body is composed of several systems that affect each other, each with its own objectives and control mechanisms.