Paper Info
Title
Machine Learning Applied to BRCA1 Hereditary Breast Cancer Data
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.
Year
DOI
Venue
2009
10.1109/WAINA.2009.165
AINA Workshops
Keywords
Field
DocType
machine learning applied,brca1 hereditary breast cancer,different profile,high risk cluster,early cancer onset,relational database,family history,different type,biological information,cancer onset,prognosticating cancer apparition,history,data mining,dna,proteins,heredity,cancer,relational databases,testing,biology,surgery,machine learning,learning artificial intelligence,polymorphism,breast cancer
Inductive logic programming,Cervical cancer,Breast cancer,Relational database,Computer science,Family history,Artificial intelligence,Cancer,Machine learning,Hereditary Breast Cancer
Conference
Citations 
PageRank 
References 
0
0.34
6
Authors
3
Name
Order
Citations
PageRank
Doncescu, A.18625.70
Baptiste Tauzain200.34
Nabil Kabbaj3184.42