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Use of Nonlinear Features for Automated Characterization of Suspicious Ovarian Tumors Using Ultrasound Images in Fuzzy Forest Framework

  • U. Rajendra Acharya
  • , U. Rajendra Acharya
  • , Ayesha Akter
  • , Pradeep Chowriappa
  • , Sumeet Dua
  • , U. Raghavendra
  • , Joel E. W. Koh
  • , Jen Hong Tan
  • , Sook Sam Leong
  • , Anushya Vijayananthan
  • , Yuki Hagiwara
  • , Marlina Tanty Ramli
  • , Kwan Hoong Ng
  • University of Malaya
  • Ngee Ann Polytechnic
  • Louisiana Tech University
  • Manipal University
  • Universiti Teknologi MARA

Research output: Contribution to journalArticlepeer-review

Original languageEnglish
Pages (from-to)1385-1402
Number of pages18
JournalInternational Journal of Fuzzy Systems
Volume20
Issue number4
DOIs
StatePublished - Apr 1 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

ASJC Scopus Subject Areas

  • Theoretical Computer Science
  • Control and Systems Engineering
  • Software
  • Information Systems
  • Computational Theory and Mathematics
  • Artificial Intelligence

Keywords

  • Data complexity
  • Fuzzy forest
  • Ovarian cancer
  • Random forest
  • Releif-F
  • k-NN

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