HOLISTICS 3.0

Human health is part of an interdependent multifaceted system. More than ever we have increasingly large amounts of data on the body, its systems and our environment. An exciting new era is dawning where we are using this valuable data together (multi-variately) with computational techniques such as machine learning to provide insights for scientific discovery, decision support, and policy formulation. Holistics 3.0 uses multiple large datasets (BigData) comprehensively describing a system together with state of the art machine learning and causality algorithms to provide insights and predictive/classification tools. Adding to the ever growing historical data records, massive amounts of new data are collected every day. With the appropriate tools we can derive this data invaluable insights for society, scientific discovery and business. The approach is relevant for insight generation and decision support in the areas of: massive datasets for public health, multiple environmental datasets for health, and health condition classification.