Search citation statements

Order By: Relevance
Select...
4
1
0
5
0

Year Published

2010
2010
2019
2019

Publication Types

Select...
3
1

Relationship

0
4

Authors

Journals

0
5
0
Order By: Relevance
“…Biomarker discovery in high-dimensional microarray data helps studying the biology of cancer [ 207 ]. When a large number of noisy, redundant genes are filtered the performance of cancer classification is improved [ 208 ]. Besides, gene selection can also cut down the cost of medical diagnoses.…”
Section: Resultsmentioning
Create an account to read the remaining citation statements from this report. You will also get access to:
  • Search over 1.2b+ citation statments to see what is being said about any topic in the research literature
  • Advanced Search to find publications that support or contrast your research
  • Citation reports and visualizations to easily see what publications are saying about each other
  • Browser extension to see Smart Citations wherever you read research
  • Dashboards to evaluate and keep track of groups of publications
  • Alerts to stay on top of citations as they happen
  • Automated reference checks to make sure you are citing reliable research in your manuscripts
  • 7 day free preview of our premium features.

Trusted by researchers and organizations around the world

Over 130,000 students researchers, and industry experts at use scite

See what students are saying

rupbmjkragerfmgwileyiopcupepmcmbcthiemesagefrontiersapsiucrarxivemeralduhksmucshluniversity-of-gavle
“…Biomarker discovery in high-dimensional microarray data helps studying the biology of cancer [ 207 ]. When a large number of noisy, redundant genes are filtered the performance of cancer classification is improved [ 208 ]. Besides, gene selection can also cut down the cost of medical diagnoses.…”
Section: Resultsmentioning
“…Wang [1] presented histogram features based neural classification for breast tissue, and Muhimmah [2] applied multi-resolution histogram features based support vector machine into mammographic density classification, and Oliver [3] classified the breast tissue density through extracting morphological and textural features and k nearest neighbor classifier. In the past research work, researcher proposes informative genes selection based cancer classification with different ways [19][20][21], and researchers presented medical image tilt correction method [22], and other relative work including DNA splicing system [23] and image recognition [24,25]. Recently, Fisher classifier is a traditional dimensionality reduction technique for feature extraction, which has been widely used and proven successful in a lot of real-world applications.…”
Section: Introductionmentioning
“…Therefore, the demanding job on the cancer gene expression data is to develop effective methods for classifying the samples into subtypes accurately with a small subset of informative genes. It makes sense that feature selection [2] is considered as a necessary pretreatment process to analyze the cancer gene expression data for reducing the dimensionality of the data.…”
Section: Introductionmentioning