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PCA-KNN for Detection of NS1 from SERS Salivary Spectra

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Intelligent Information and Database Systems (ACIIDS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10752))

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Abstract

K-Nearest Neighbor (kNN) has shown its strong capability in pattern recognition, classification and machine learning applications. In this paper, kNN was used to distinguish between Non-structural protein 1 (NS1) positive and NS1 negative dengue patients from salivary Raman spectra. The presence of NS1 was detected in the saliva of dengue infected subjects. It was found Raman active, producing a molecular Raman fingerprint. Surface Enhanced Raman Spectroscopic (SERS) technique was adopted in obtaining the NS1 Raman spectra dataset. Performance of kNN with different K-values, optimized with Scree, Cumulative Percentage Variance (CPV) and Eigenvalue One Criterion (EOC) stopping criteria, was investigated and compared in term of sensitivity, specificity, accuracy and kappa. The best performance is found with the use of CPV stopping criteria and a K-value of 5, which attained an accuracy of 84.5% and kappa of 0.69.

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Acknowledgment

The author would like to thank the Ministry of Education (MOE) of Malaysia, for providing the research funding 600-RMI/ERGS 5/3 (20/2013); the Research Management Institute, and the Faculty of Electrical Engineering, Universiti Teknologi MARA, Malaysia, for the support and assistance given to the authors in carrying out this research.

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Authors and Affiliations

  1. Faculty of Electrical Engineering and Computational Intelligence EK, Pharmaceutical & Lifesciences Communities of Research, Universiti Teknologi MARA, Shah Alam, Malaysia

    N. H. Othman, Khuan Y. Lee, A. R. M. Radzol & W. Mansor

  2. Infectious Unit, Pulau Penang General Hospital, George Town, Malaysia

    P. S. Wong

  3. Seberang Prai General Hospital, Seberang Perai, Malaysia

    I. Looi

Authors
  1. N. H. Othman
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  2. Khuan Y. Lee
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  3. A. R. M. Radzol
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  4. W. Mansor
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  5. P. S. Wong
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  6. I. Looi
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Corresponding author

Correspondence to Khuan Y. Lee .

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Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Quang Binh University, Dong Hoi City, Vietnam

    Duong Hung Hoang

  3. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  4. Rutgers University, Piscataway, New Jersey, USA

    Hoang Pham

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Othman, N.H., Lee, K.Y., Radzol, A.R.M., Mansor, W., Wong, P.S., Looi, I. (2018). PCA-KNN for Detection of NS1 from SERS Salivary Spectra. In: Nguyen, N., Hoang, D., Hong, TP., Pham, H., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Computer Science(), vol 10752. Springer, Cham. https://doi.org/10.1007/978-3-319-75420-8_32

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  • DOI: https://doi.org/10.1007/978-3-319-75420-8_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75419-2

  • Online ISBN: 978-3-319-75420-8

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