title: Cancer risk analysis in families with hereditary nonpolyposis colorectal cancer.
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.
authors.affiliation: BIOCORE, Faculty of Engineering and Computing, Coventry University, UK. m.kokuer@coventry.ac.uk
authors.forename: Münevver
authors.initials: M
authors.lastname: Köküer
authors.forename: Raouf N G
authors.initials: RN
authors.lastname: Naguib
authors.forename: Peter
authors.initials: P
authors.lastname: Jancovic
authors.forename: H Banfield
authors.initials: HB
authors.lastname: Younghusband
authors.forename: Roger C
authors.initials: RC
authors.lastname: Green
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003123:Colorectal Neoplasms, Hereditary Nonpolyposis / Q000175:diagnosis / Q000453:epidemiology* / Q000235:genetics*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005190:Family; D020022:Genetic Predisposition to Disease / Q000453:epidemiology* / Q000235:genetics*; D005820:Genetic Testing / Q000379:methods*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods; D010375:Pedigree; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D006113:United Kingdom / Q000453:epidemiology