Machine Learning Approach for Predicting Metastatic Sitesof of Prostate Cancer

被引：0

作者：

El Amsy, Tarik ^{[1
]}

机构：

[1] Al Univ Sci & Technol, Abu Dhabi, U Arab Emirates

来源：

ACM-BCB'19: PROCEEDINGS OF THE 10TH ACM INTERNATIONAL CONFERENCE ON BIOINFORMATICS, COMPUTATIONAL BIOLOGY AND HEALTH INFORMATICS | 2019年

关键词：

Prostate cancer; survival; biomarker genes; machine learning; classification; clustering;

D O I：

10.1145/3307339.3343477

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Analyzing Genomic profiles of prostate cancer patients with the similar metastatic site may unveil the progression mechanism of cancer and assist in the diagnose and the treatment of cancer. In this model, we propose a machine learning approach based on gene expression and copy number alterations for cohorts of prostate cancer with different metastatic sites.

引用

页码：626 / 626

页数：1

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