DocumentCode
2308897
Title
Machine Learning Applied to BRCA1 Hereditary Breast Cancer Data
Author
Doncescu, Andrei ; Tauzain, Baptiste ; Kabbaj, Nabil
Author_Institution
CNRS, Univ. of Toulouse, Toulouse, France
fYear
2009
fDate
26-29 May 2009
Firstpage
942
Lastpage
947
Abstract
This research aims to provide a tool to doctors in order to help for diagnosis of BRCA1 hereditary breast cancer. Our goal is to determine, if possible, profiles that are responsible for early cancer onset. In order to extract knowledge from the biological information above we will create a relational database that will allow prognosticating cancer apparition. We want to determine different types responsible for different profiles of cancer onset thanks to machine learning programs. The prognostic will rely on polymorphisms of a gene, BRCA1, but on family history as well. The machine learning software(s) will be used as a tool by doctors as a help for diagnosis. This tool will be used in order to determine if these patients are member of a high risk cluster, an early occurring cancer.
Keywords
cancer; learning (artificial intelligence); medical computing; relational databases; BRCA1 hereditary breast cancer data; biological information; cancer apparition prognostication; machine learning; relational database; Breast cancer; Cervical cancer; DNA; Data mining; Genetic mutations; History; Machine learning; Proteins; Surgery; Testing; BRCA1; Heredity; breast cancer; inductive logic programming; polymorphism;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Information Networking and Applications Workshops, 2009. WAINA '09. International Conference on
Conference_Location
Bradford
Print_ISBN
978-1-4244-3999-7
Electronic_ISBN
978-0-7695-3639-2
Type
conf
DOI
10.1109/WAINA.2009.165
Filename
5136772
Link To Document