Sparse feature selection for classification and prediction of metastasis in endometrial cancer.
about
Selected research articles from the 2016 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC).Sparse Supervised Classification Methods Predict and Characterize Nanomaterial Exposures: Independent Markers of MWCNT Exposures.Non-Coding RNAs and Endometrial Cancer.Structural neuroimaging as clinical predictor: A review of machine learning applications
P2860
Sparse feature selection for classification and prediction of metastasis in endometrial cancer.
description
2017 nî lūn-bûn
@nan
2017年の論文
@ja
2017年学术文章
@wuu
2017年学术文章
@zh-cn
2017年学术文章
@zh-hans
2017年学术文章
@zh-my
2017年学术文章
@zh-sg
2017年學術文章
@yue
2017年學術文章
@zh
2017年學術文章
@zh-hant
name
Sparse feature selection for c ...... astasis in endometrial cancer.
@ast
Sparse feature selection for c ...... astasis in endometrial cancer.
@en
type
label
Sparse feature selection for c ...... astasis in endometrial cancer.
@ast
Sparse feature selection for c ...... astasis in endometrial cancer.
@en
prefLabel
Sparse feature selection for c ...... astasis in endometrial cancer.
@ast
Sparse feature selection for c ...... astasis in endometrial cancer.
@en
P2093
P2860
P1433
P1476
Sparse feature selection for c ...... tastasis in endometrial cancer
@en
P2093
Burook Misganaw
Carolyn K McCourt
David G Mutch
Floor J Backes
Jayanthi S Lea
Kathleen N Moore
Mathukumalli Vidyasagar
Michael A White
Nitin K Singh
Todd P Boren
P2860
P356
10.1186/S12864-017-3604-Y
P407
P433
P577
2017-03-27T00:00:00Z