Analysis of Autism Prevalence and Neurotoxins Using Combinatorial Fusion and Association Rule Mining

Authors:
Christina Schweikert;Yanjun Li;David Dayya;David Yens;Martin Torrents;D. Frank Hsu
Affiliations:
-;-;-;-;-;-
Venue:
BIBE '09 Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering
Year:
2009

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Abstract

The increase in autism prevalence has been the motivation for much research which has produced various theories for its causation. Genetic and environmental factors have been investigated. An area of focus is the affect of exposure to neurotoxins, such as mercury and lead, during critical stages in a child’s early development. In this study we apply Combinatorial Fusion Analysis (CFA) and Association Rule Mining (ARM) to autism prevalence, mercury, and lead data to generate hypotheses and explore possible associations.