Table 3.

Big data modeling techniques

Method	Advantages	Disadvantages
Neural Networks	Discover non-linear relationships. Can assess multi-level interactions	“Black Box” to clinicians; hard to implement into a DSS*
Random Forests	Finds most probable solution set; robust against scaling influences	Not always best in terms of prediction; hard to implement into a DSS
Cluster Analysis	Finds groups of very similar patients; exploratory analysis	Unsupervised technique
Principal Components Analysis	Uncovers the variables contributing the most to outcome variation	Not amenable to binary outcomes; assumes additive relationship
Support Vector Machines	Robust against statistical assumptions	Difficult to implement into a DSS