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 :
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