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» Using evolvable genetic cellular automata to model breast ca...
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GPEM
2007
116views more  GPEM 2007»
13 years 4 months ago
Using evolvable genetic cellular automata to model breast cancer
Cancer is an evolutionary process; mutated cells are selected for abnormal growth and survivability. Here, a computer simulation is used to model ductal carcinoma in situ (DCIS), ...
Armand Bankhead, Robert B. Heckendorn
CIKM
2009
Springer
13 years 11 months ago
Multivariate classification of urine metabolome profiles for breast cancer diagnosis
Background: Diagnosis techniques using urine are non-invasive, inexpensive, and easy to perform in clinical settings. The metabolites in urine, as the end products of cellular pro...
Younghoon Kim, Imhoi Koo, Byung Hwa Jung, Bong Chu...
EH
2002
IEEE
139views Hardware» more  EH 2002»
13 years 9 months ago
Evolving Cellular Automata to Model Fluid Flow in Porous Media
Fluid flow in porous media is a dynamic process that is traditionally modeled using PDE (Partial Differential Equations). In this approach, physical properties related to fluid fl...
Tina Yu, Seong Lee
IJON
2006
146views more  IJON 2006»
13 years 4 months ago
Feature selection and classification using flexible neural tree
The purpose of this research is to develop effective machine learning or data mining techniques based on flexible neural tree FNT. Based on the pre-defined instruction/operator se...
Yuehui Chen, Ajith Abraham, Bo Yang
GECCO
2005
Springer
134views Optimization» more  GECCO 2005»
13 years 10 months ago
Predicting mining activity with parallel genetic algorithms
We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa ...
Sam Talaie, Ryan E. Leigh, Sushil J. Louis, Gary L...