Gene expression profiling of breast cancer survivability by pooled cDNA microarray analysis using logistic regression, artificial neural networks and decision trees

CHUR > College Computer Science and Informatics > Department of Bioinformatics > Journal Articles > Item 987654321/30746

Please use this identifier to cite or link to this item: http://chur.chu.edu.tw/handle/987654321/30746

Title:	Gene expression profiling of breast cancer survivability by pooled cDNA microarray analysis using logistic regression, artificial neural networks and decision trees
Authors:	胡光宇 Hu, Kuang-Yu
Contributors:	生物資訊學系 Bioinformatics
Keywords:	乳癌;微陣列晶片;類神經網路;邏輯斯迴歸;決策樹 Breast Cancer;Microarray;Artificial Neural Network;Logistic Regression;Decision Tree
Date:	2013
Issue Date:	2014-06-27 01:09:06 (UTC+8)
Abstract:	BACKGROUND: Microarray technology can acquire information about thousands of genes simultaneously. We analyzed published breast cancer microarray databases to predict five-year recurrence and compared the performance of three data mining algorithms of art
Appears in Collections:	[Department of Bioinformatics] Journal Articles

Files in This Item:

File	Description	Size	Format
p_s121_0041.pdf		27Kb	Adobe PDF	358	View/Open