Title :
Cancer Risk Analysis in Families With Hereditary Nonpolyposis Colorectal Cancer
Author :
Köküer, Münevver ; Naguib, Raouf N G ; Jancovic, P. ; Younghusband, H. Banfield ; Green, Roger C.
Author_Institution :
BIOCORE, Coventry Univ.
fDate :
7/1/2006 12:00:00 AM
Abstract :
Colorectal cancer (CRC) is one of the most common fatal cancers in developed countries and represents a significant public-health issue. About 3%-5% of patients with CRC have hereditary nonpolyposis colorectal cancer (HNPCC). Cancer morbidity and mortality can be reduced if early and intensive screening is pursued. However, despite advances in screening, 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/assessed, then only the high-risk fraction of the population would undergo intensive screening. This identification is currently performed by a genetic counselor/physician who makes the decision based on some pre-defined criteria. Here, we report on a system to identify the risk of a family having HNPCC based on its history. We compare artificial neural networks and statistical approaches for assessing the risk of a family having HNPCC and discuss the experimental results obtained by these two approaches
Keywords :
cancer; genetics; medical computing; principal component analysis; regression analysis; risk analysis; self-organising feature maps; tumours; ANN; PCA; artificial neural networks; cancer morbidity; cancer mortality; cancer risk analysis; cancer risk assessment; fatal cancers; hereditary nonpolyposis colorectal cancer; intensive screening; logistic regression; pedigree analysis; population-wide genetic screening; principal component analysis; self-organizing maps; statistical approach; Artificial neural networks; Cancer; Colon; Computer errors; Cyclic redundancy check; Diseases; Genetics; History; Principal component analysis; Risk analysis; Artificial neural networks (ANNs); cancer risk assessment; hereditary nonpolyposis colorectal cancer (HNPCC); logistic regression (LR); pedigree analysis; principal component analysis (PCA); self-organizing maps (SOM);
Journal_Title :
Information Technology in Biomedicine, IEEE Transactions on
DOI :
10.1109/TITB.2006.872054