Support Vector Machine - Recursive Feature Elimination (SVM-RFE) for Selection of MicroRNA Expression Features of Breast Cancer

被引：0
|
作者：
Adorada, Amazona [1 ]
Permatasari, Ratih [1 ]
Wirawan, Panji Wisnu [1 ]
Wibowo, Adi [1 ]
Sujiwo, Adi [2 ]
机构：
[1] Diponegoro Univ, Dept Informat, Semarang, Indonesia
[2] Nagoya Univ, Dept Informat Syst, Nagoya, Aichi, Japan
来源：
2018 2ND INTERNATIONAL CONFERENCE ON INFORMATICS AND COMPUTATIONAL SCIENCES (ICICOS) | 2018年
关键词：
Feature Selection; SVM-RFE; Breast Cancer; MicroRNA; GENE SELECTION;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Cancer is still a major problem for people today because it is one of the biggest causes of death in the world. Based on GLOBOCAN data in 2012, breast cancer accounted for the world's largest cancer mortality rate in women by 14.7% with total deaths amounting to 521,907 from 3,548,190 cases of cancer in the world. The high mortality rate is affected by the absence of sufficient early detection of cancer. MicroRNAs play an essential role in regulating cell division cycles, apoptosis, senescence, migration and cell invasion, and metastasis. The expression of microRNA in breast cancer shows a pattern compared to normal breasts, thus indicating its role as a potential diagnostic marker. However, not all microRNA profiles have a significant role in cancer detection. In this paper, we applied the support vector machine - recursive feature elimination (SVM-RFE) and univariate selection for feature selection of microRNA expression in breast cancer. Several experiments were conducted to select ten features with the highest ranking; therefore, it is expected to obtain a unique feature as a unique feature of breast cancer. Based on experimental results, this study obtained recommended the essential MicroRNA features for cancer analysis and biomarkers.
引用
收藏
页码：165 / 168
页数：4
相关论文
共 50 条
  • [1] Hepatitis Detection using Random Forest based on SVM-RFE (Recursive Feature Elimination) Feature Selection and SMOTE
    Krisnabayu, Rifky Yunus
    Ridok, Achmad
    Budi, Agung Setia
    [J]. PROCEEDINGS OF 2021 INTERNATIONAL CONFERENCE ON SUSTAINABLE INFORMATION ENGINEERING AND TECHNOLOGY, SIET 2021, 2021, : 151 - 156
  • [2] Multiple SVM-RFE for gene selection in cancer classification with expression data
    Duan, KB
    Rajapakse, JC
    Wang, HY
    Azuaje, F
    [J]. IEEE TRANSACTIONS ON NANOBIOSCIENCE, 2005, 4 (03) : 228 - 234
  • [3] A variant of SVM-RFE for gene selection in cancer classification with expression data
    Duan, KB
    Rajapakse, JC
    [J]. PROCEEDINGS OF THE 2004 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, 2004, : 49 - 55
  • [4] PSO based feature selection of gene for cancer classification using SVM-RFE
    Kavitha, K. R.
    Nair, Harishankar U.
    Akhil, M. C.
    [J]. 2018 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI), 2018, : 1012 - 1016
  • [5] Transferability of Recursive Feature Elimination (RFE)-Derived Feature Sets for Support Vector Machine Land Cover Classification
    Ramezan, Christopher A. A.
    [J]. REMOTE SENSING, 2022, 14 (24)
  • [6] Feature clustering based support vector machine recursive feature elimination for gene selection
    Huang, Xiaojuan
    Zhang, Li
    Wang, Bangjun
    Li, Fanzhang
    Zhang, Zhao
    [J]. APPLIED INTELLIGENCE, 2018, 48 (03) : 594 - 607
  • [7] Feature clustering based support vector machine recursive feature elimination for gene selection
    Xiaojuan Huang
    Li Zhang
    Bangjun Wang
    Fanzhang Li
    Zhao Zhang
    [J]. Applied Intelligence, 2018, 48 : 594 - 607
  • [8] Correlated Based SVM-RFE as Feature Selection for Cancer Classification Using Microarray Databases
    Rustam, Z.
    Maghfirah, N.
    [J]. PROCEEDINGS OF THE 3RD INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2017 (ISCPMS2017), 2018, 2023
  • [9] A Model Using Support Vector Machines Recursive Feature Elimination (SVM-RFE) Algorithm to Classify Whether COPD Patients Have Been Continuously Managed According to GOLD Guidelines
    Xia, Jie
    Sun, Lina
    Xu, Suqin
    Xiang, Qiu
    Zhao, Jianping
    Xiong, Weining
    Xu, Yongjian
    Chu, Shuyuan
    [J]. INTERNATIONAL JOURNAL OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE, 2020, 15 : 2779 - 2786
  • [10] Multi-scoring Feature selection method based on SVM-RFE for prostate cancer diagnosis
    Albashish, Dheeb
    Sahran, Shahnorbanun
    Abdullah, Azizi
    Adam, Afzan
    Abd Shukor, Nordashima
    Pauzi, Suria Hayati Md
    [J]. 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND INFORMATICS 2015, 2015, : 682 - 686
12345