Title :
Poster: Applying data mining algorithms to early detection of liver cancer
Author :
Pinheiro, Fabiola M R ; Kuo, Mu-Hsing
Author_Institution :
Sch. of Health Inf. Sci., Univ. of Victoria, Victoria, BC, Canada
Abstract :
According to the World Health Organization, cancer is leading cause of deaths globally. Among all types cancer, liver cancer has the lowest survivability, with approximately 1 million deaths each year. Its rising incidence in the past decade is projected to continue is associated with varying demographic factors. Data mining can be of great utility in better understanding which risk factors are associated with increased incidence of liver cancer, as suggested by previous studies.
Keywords :
cancer; data mining; liver; medical computing; World Health Organization; data mining algorithms; early liver cancer detection; risk factors; Algorithm design and analysis; Association rules; Cancer; Liver; Surgery; FP-growth; apriori; association algorithm; data mining; liver cancer;
Conference_Titel :
Computational Advances in Bio and Medical Sciences (ICCABS), 2012 IEEE 2nd International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4673-1320-9
Electronic_ISBN :
978-1-4673-1319-3
DOI :
10.1109/ICCABS.2012.6182656