Chapter - Auto Contractive Maps, H Function and Maximally Regular Graph - Application

Auto Contractive Maps, H Function and Maximally Regular Graph - Application

Pp: 42-47 (6)

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Abstract

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.

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