In this chapter we describe a new mapping method able to find out connectivity traces among variables
thanks to an artificial adaptive system, the Auto-Contractive Map (Auto-CM), able to define the
strength of the associations of each variable with all the others in a dataset. After the training phase, the
weights matrix of the Auto-CM represents the map of the main connections between the variables. We apply
this new approach to explore the possible association of multiple variables within two different clinical studies:
the African American Antiplatelet Stroke Study (AAASPS), a large clinical trial comparing the preventive
effect of two different anti platelet agents for recurrent stroke, myocardial infarction and death, and a
smaller study, the Aspirin Response Study (ARS), wherein the genetic predisposition to aspirin response as
measured by inhibition of platelet aggregation measured ex vivo was determined in patients taking aspirin for
the prevention of thrombotic vascular occlusion.
Keywords: Artificial Adaptive Systems, Artificial Neural Networks, Connectivity Map, Non-linearity, Auto-
CM.
