Machine Learning Applied to BRCA1 Hereditary Breast Cancer Data

A. Doncescu, Baptiste Tauzain, N. Kabbaj
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引用次数: 2

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.
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机器学习应用于BRCA1遗传性乳腺癌数据
本研究旨在为医生提供一种工具,以帮助BRCA1遗传性乳腺癌的诊断。如果可能的话,我们的目标是确定导致癌症早期发病的基因。为了从以上的生物信息中提取知识,我们将创建一个关系数据库,用于预测癌症的出现。我们希望通过机器学习程序来确定导致不同癌症发病概况的不同类型。预后将依赖于基因BRCA1的多态性,但也依赖于家族史。机器学习软件将被医生用作辅助诊断的工具。该工具将用于确定这些患者是否属于高风险群体,即早期发生的癌症。
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