A comparison of multi-layer neural network and logistic regression in hereditary non-polyposis colorectal cancer risk assessment.
Hereditary non-polyposis colorectal cancer (HN-PCC) is one of the most common autosomal dominant diseases in developed countries. Here, we report on a system to identify the risk of a family having HNPCC based on its history. This is important since population-wide genetic screening for HNPCC is not currently considered feasible due to its complexity and expense. If the risk of a family having HNPCC can be identified/asessed, then only the high risk fraction of the population would undergo intensive screening. Here, we have developed a Multi-Layer Feed-Forward Neural Network to classify families into high-, intermediate- and low-risk categories and compared the result with the benchmark logistic regression model.
Kokuer
Munevver
M
BIOCORE, School of MIS, Coventry University, Coventry, UK.
G Naguib
Raouf
R
Jancovic
Peter
P
Banfield Younghusband
H
H
Green
Roger
R