Risk classification of cancer survival using ANN with gene expression data from multiple laboratories.
about
Logic Learning Machine and standard supervised methods for Hodgkin's lymphoma prognosis using gene expression data and clinical variables.Machine learning and systems genomics approaches for multi-omics data.Machine learning applications in cancer prognosis and predictionIdentification of Gene Expression Pattern Related to Breast Cancer Survival Using Integrated TCGA Datasets and Genomic Tools.Feature selection through validation and un-censoring of endovascular repair survival data for predicting the risk of re-intervention.Using multiple classifiers for predicting the risk of endovascular aortic aneurysm repair re-intervention through hybrid feature selection.Ensemble Methods with Voting Protocols Exhibit Superior Performance for Predicting Cancer Clinical Endpoints and Providing More Complete Coverage of Disease-Related Genes.Multiple Machine Learnings Revealed Similar Predictive Accuracy for Prognosis of PNETs from the Surveillance, Epidemiology, and End Result DatabaseA Deep Neural Network Model using Random Forest to Extract Feature Representation for Gene Expression Data Classification
P2860
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P2860
Risk classification of cancer survival using ANN with gene expression data from multiple laboratories.
description
2014 nî lūn-bûn
@nan
2014 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի փետրվարին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
Risk classification of cancer ...... ta from multiple laboratories.
@ast
Risk classification of cancer ...... ta from multiple laboratories.
@en
type
label
Risk classification of cancer ...... ta from multiple laboratories.
@ast
Risk classification of cancer ...... ta from multiple laboratories.
@en
prefLabel
Risk classification of cancer ...... ta from multiple laboratories.
@ast
Risk classification of cancer ...... ta from multiple laboratories.
@en
P1476
Risk classification of cancer ...... ata from multiple laboratories
@en
P2093
Wan-Chi Ke
Yen-Chen Chen
P356
10.1016/J.COMPBIOMED.2014.02.006
P577
2014-02-22T00:00:00Z