Data integration model for cancer subtype identification using kernel dimensionality reduction-support vector machine (KDR-SVM)

Ito Wasito; Aulia N. Istiqlal; Indra Budi

Data integration model for cancer subtype identification using kernel dimensionality reduction-support vector machine (KDR-SVM)

Ito Wasito, Aulia N. Istiqlal, Indra Budi

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

In this paper, an integration model of cancer patients data types such as microarray DNA and clinical data will be experimentally explored. The data of integration will be used for cancer subtype identification using kernel based classification methods which is the extension of Support Vector Machine (SVM) approach with Kernel Dimensionality Reduction (KDR). KDR-SVM method will be implemented in Lymphoma cancer database and the relevant clinical information. Data type representation will be modeled in an appropriate kernel matrix. The results of the experiment show that the KDR-10 dimensions and data integration can improve the accuracy of the identification of subtype cancer.

Original language	English
Title of host publication	Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012
Pages	876-880
Number of pages	5
Publication status	Published - 2012
Event	2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012 - Seoul, Korea, Republic of Duration: 3 Dec 2012 → 5 Dec 2012

Publication series

Name	Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012

Conference

Conference	2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012
Country/Territory	Korea, Republic of
City	Seoul
Period	3/12/12 → 5/12/12

Keywords

Clinical Data
Data Integration
Kernel Dimensionality Reduction
Kernel Matrix
Microarray data
Support Vector Machine

UN SDGs

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

Cite this

Wasito, I., Istiqlal, A. N., & Budi, I. (2012). Data integration model for cancer subtype identification using kernel dimensionality reduction-support vector machine (KDR-SVM). In Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012 (pp. 876-880). Article 6530459 (Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012).

Wasito, Ito ; Istiqlal, Aulia N. ; Budi, Indra. / Data integration model for cancer subtype identification using kernel dimensionality reduction-support vector machine (KDR-SVM). Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012. 2012. pp. 876-880 (Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012).

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title = "Data integration model for cancer subtype identification using kernel dimensionality reduction-support vector machine (KDR-SVM)",

abstract = "In this paper, an integration model of cancer patients data types such as microarray DNA and clinical data will be experimentally explored. The data of integration will be used for cancer subtype identification using kernel based classification methods which is the extension of Support Vector Machine (SVM) approach with Kernel Dimensionality Reduction (KDR). KDR-SVM method will be implemented in Lymphoma cancer database and the relevant clinical information. Data type representation will be modeled in an appropriate kernel matrix. The results of the experiment show that the KDR-10 dimensions and data integration can improve the accuracy of the identification of subtype cancer.",

keywords = "Clinical Data, Data Integration, Kernel Dimensionality Reduction, Kernel Matrix, Microarray data, Support Vector Machine",

author = "Ito Wasito and Istiqlal, {Aulia N.} and Indra Budi",

year = "2012",

language = "English",

isbn = "9788994364216",

series = "Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012",

pages = "876--880",

booktitle = "Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012",

note = "2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012 ; Conference date: 03-12-2012 Through 05-12-2012",

}

Wasito, I, Istiqlal, AN & Budi, I 2012, Data integration model for cancer subtype identification using kernel dimensionality reduction-support vector machine (KDR-SVM). in Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012., 6530459, Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012, pp. 876-880, 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012, Seoul, Korea, Republic of, 3/12/12.

Data integration model for cancer subtype identification using kernel dimensionality reduction-support vector machine (KDR-SVM). / Wasito, Ito; Istiqlal, Aulia N.; Budi, Indra.
Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012. 2012. p. 876-880 6530459 (Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Data integration model for cancer subtype identification using kernel dimensionality reduction-support vector machine (KDR-SVM)

AU - Wasito, Ito

AU - Istiqlal, Aulia N.

AU - Budi, Indra

PY - 2012

Y1 - 2012

N2 - In this paper, an integration model of cancer patients data types such as microarray DNA and clinical data will be experimentally explored. The data of integration will be used for cancer subtype identification using kernel based classification methods which is the extension of Support Vector Machine (SVM) approach with Kernel Dimensionality Reduction (KDR). KDR-SVM method will be implemented in Lymphoma cancer database and the relevant clinical information. Data type representation will be modeled in an appropriate kernel matrix. The results of the experiment show that the KDR-10 dimensions and data integration can improve the accuracy of the identification of subtype cancer.

AB - In this paper, an integration model of cancer patients data types such as microarray DNA and clinical data will be experimentally explored. The data of integration will be used for cancer subtype identification using kernel based classification methods which is the extension of Support Vector Machine (SVM) approach with Kernel Dimensionality Reduction (KDR). KDR-SVM method will be implemented in Lymphoma cancer database and the relevant clinical information. Data type representation will be modeled in an appropriate kernel matrix. The results of the experiment show that the KDR-10 dimensions and data integration can improve the accuracy of the identification of subtype cancer.

KW - Clinical Data

KW - Data Integration

KW - Kernel Dimensionality Reduction

KW - Kernel Matrix

KW - Microarray data

KW - Support Vector Machine

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M3 - Conference contribution

AN - SCOPUS:84881143897

SN - 9788994364216

T3 - Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012

SP - 876

EP - 880

BT - Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012

T2 - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012

Y2 - 3 December 2012 through 5 December 2012

ER -

Wasito I, Istiqlal AN, Budi I. Data integration model for cancer subtype identification using kernel dimensionality reduction-support vector machine (KDR-SVM). In Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012. 2012. p. 876-880. 6530459. (Proceedings - 2012 7th International Conference on Computing and Convergence Technology (ICCIT, ICEI and ICACT), ICCCT 2012).

Data integration model for cancer subtype identification using kernel dimensionality reduction-support vector machine (KDR-SVM)

Abstract

Publication series

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Keywords

UN SDGs

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