Detecting biomarkers for major adverse cardiac events using SVM with PLS feature selection and extraction

Zheng Yin; Xiaobo Zhou; Honghui Wang; Youxian Sun; Stephen T C Wong

doi:10.1007/978-3-540-72393-6_130

Detecting biomarkers for major adverse cardiac events using SVM with PLS feature selection and extraction

Zheng Yin, Xiaobo Zhou, Honghui Wang, Youxian Sun, Stephen T C Wong

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

Abstract

Detection of biomarkers capable of predicting a patient's risk of major adverse cardiac events (MACE) is of clinical significance. Due to the high dynamic range of the protein concentration in human blood, applying proteomics techniques for protein profiling can generate large arrays of data for development of optimized clinical biomarker panels. The objective of this study is to discover an optimized subset of biomarkers for predicting risk of MACE containing less than ten biomarkers. In this paper, we connect linear SVM with PLS feature selection and extraction. A simplified PLS algorithm selects a subset of biomarkers and extracts latent variables and prediction performance of linear SVM is dramatically improved. The proposed method is compared with a widely used PLS-Logistic Discriminant solution and several other reported methods based on the MACE prediction experiments.

Original language	English (US)
Title of host publication	Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
Publisher	Springer-Verlag
Pages	1097-1106
Number of pages	10
Edition	PART 2
ISBN (Print)	9783540723929
DOIs	https://doi.org/10.1007/978-3-540-72393-6_130
State	Published - 2007
Event	4th International Symposium on Neural Networks, ISNN 2007 - Nanjing, China Duration: Jun 3 2007 → Jun 7 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	4492 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	4th International Symposium on Neural Networks, ISNN 2007
Country/Territory	China
City	Nanjing
Period	6/3/07 → 6/7/07

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-540-72393-6_130

Cite this

Yin, Z., Zhou, X., Wang, H., Sun, Y., & Wong, S. T. C. (2007). Detecting biomarkers for major adverse cardiac events using SVM with PLS feature selection and extraction. In Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings (PART 2 ed., pp. 1097-1106). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4492 LNCS, No. PART 2). Springer-Verlag. https://doi.org/10.1007/978-3-540-72393-6_130

Detecting biomarkers for major adverse cardiac events using SVM with PLS feature selection and extraction. / Yin, Zheng; Zhou, Xiaobo; Wang, Honghui et al.
Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 2. ed. Springer-Verlag, 2007. p. 1097-1106 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4492 LNCS, No. PART 2).

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

Yin, Z, Zhou, X, Wang, H, Sun, Y & Wong, STC 2007, Detecting biomarkers for major adverse cardiac events using SVM with PLS feature selection and extraction. in Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 4492 LNCS, Springer-Verlag, pp. 1097-1106, 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, 6/3/07. https://doi.org/10.1007/978-3-540-72393-6_130

Yin Z, Zhou X, Wang H, Sun Y, Wong STC. Detecting biomarkers for major adverse cardiac events using SVM with PLS feature selection and extraction. In Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 2 ed. Springer-Verlag. 2007. p. 1097-1106. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-540-72393-6_130

Yin, Zheng ; Zhou, Xiaobo ; Wang, Honghui et al. / Detecting biomarkers for major adverse cardiac events using SVM with PLS feature selection and extraction. Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 2. ed. Springer-Verlag, 2007. pp. 1097-1106 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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abstract = "Detection of biomarkers capable of predicting a patient's risk of major adverse cardiac events (MACE) is of clinical significance. Due to the high dynamic range of the protein concentration in human blood, applying proteomics techniques for protein profiling can generate large arrays of data for development of optimized clinical biomarker panels. The objective of this study is to discover an optimized subset of biomarkers for predicting risk of MACE containing less than ten biomarkers. In this paper, we connect linear SVM with PLS feature selection and extraction. A simplified PLS algorithm selects a subset of biomarkers and extracts latent variables and prediction performance of linear SVM is dramatically improved. The proposed method is compared with a widely used PLS-Logistic Discriminant solution and several other reported methods based on the MACE prediction experiments.",

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Detecting biomarkers for major adverse cardiac events using SVM with PLS feature selection and extraction

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