Classification of lung cancer using ensemble-based feature selection and machine learning methods.
about
On Predicting lung cancer subtypes using 'omic' data from tumor and tumor-adjacent histologically-normal tissue.Finding disagreement pathway signatures and constructing an ensemble model for cancer classificationMachine learning for epigenetics and future medical applications.Modified Bat Algorithm for Feature Selection with the Wisconsin Diagnosis Breast Cancer (WDBC) DatasetA systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer.Targeting sphingosine-1-phosphate signaling in lung diseases.Discriminating cirRNAs from other lncRNAs using a hierarchical extreme learning machine (H-ELM) algorithm with feature selection.Oblique rotation of factors: a novel pattern recognition strategy to classify fluorescence excitation-emission matrices of human blood plasma for early diagnosis of colorectal cancer.A Deep Neural Network Model using Random Forest to Extract Feature Representation for Gene Expression Data Classification
P2860
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P2860
Classification of lung cancer using ensemble-based feature selection and machine learning methods.
description
2014 nî lūn-bûn
@nan
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
2014年论文
@zh
2014年论文
@zh-cn
name
Classification of lung cancer ...... and machine learning methods.
@en
type
label
Classification of lung cancer ...... and machine learning methods.
@en
prefLabel
Classification of lung cancer ...... and machine learning methods.
@en
P2093
P2860
P356
P1433
P1476
Classification of lung cancer ...... and machine learning methods.
@en
P2093
Jianlin Shao
Jiexia Zhang
Qing Zhang
Sai-Ming Ngai
Zhihua Cai
P2860
P304
P356
10.1039/C4MB00659C
P577
2014-12-16T00:00:00Z