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Applying Fuzzy ART in medical diagnosis of cancers

  • Fu Jen Catholic University
    ,
  • Johns Hopkins University
    ,
Scholary Output:
Chapter in Book/Report/Conference proceeding
Conference contribution

Sustainable Development Goals

  • SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well

Abstract

Many researchers have used proteomic mass spectrometry for cancer detection and with various types of data preprocessing and classification methods to overcome data complexities. This research focuses on discovering different cancers display their unique proteomic patterns or have similar patterns with others. To meet this goal, this study introduces a complete data preprocessing procedure and applies a Fuzzy ART clustering method to differentiate the patterns among multiple cancer diseases. This approach shows the potential of separating cancer patterns from healthy patterns, as well as among different types of cancers.

Publication Information

Output type

Scholary Output:
Chapter in Book/Report/Conference proceeding
Conference contribution

Original language

English (US)

Article number

5580939

Pages from-to (Number of pages)

Pages 1084-1089 (6 pages)

Publication milestones

  • Published - 2010

Publication status

Published - 2010

Publisher

IEEE Computer Society

Publication series

  • Publication series name: 2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010
    Volume: 3
9781424465262

Publication IDs

  • Scopus: 78149355244

Host publication title

2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010

Publication metrics

Metrics

SciVal
citations
1
SciVal
FWCI
0.42
SciVal
Author count
4
SciVal
Paper percentile
33
Scopus
citations
Fractional count
1
Fractional count
0.25
Fractional count
3
Fractional count
0.75
Fractional count
1
Fractional count
1