Title :
Analysis of Autism Prevalence and Neurotoxins Using Combinatorial Fusion and Association Rule Mining
Author :
Schweikert, Christina ; Li, Yanjun ; Dayya, David ; Yens, David ; Torrents, Martin ; Hsu, D. Frank
Author_Institution :
Dept. of Comput. & Inf. Sci., Fordham Univ., Bronx, NY, USA
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 childpsilas 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.
Keywords :
bioinformatics; brain; data mining; lead; medical computing; medical disorders; mercury (metal); neurophysiology; toxicology; Hg; Pb; association rule mining; autism prevalence analysis; bioinformatics; combinatorial fusion analysis; data mining; multiple scoring systems; neurotoxins; rank-score characteristic graph; Association rules; Autism; Bioinformatics; Data mining; Environmental factors; Genetics; Information analysis; Pediatrics; USA Councils; Variable speed drives; Association Rule Mining; Combinatorial Fusion Analysis (CFA); Data Mining; Information Fusion; Multiple Scoring Systems; Rank-Score Characteristic (RSC) graph; autism; lead; mercury; neurotoxins;
Conference_Titel :
Bioinformatics and BioEngineering, 2009. BIBE '09. Ninth IEEE International Conference on
Conference_Location :
Taichung
Print_ISBN :
978-0-7695-3656-9
DOI :
10.1109/BIBE.2009.69
