Newborn screening for phenylketonuria: Machine learning vs clinicians

Wei Hsin Chen; Han Ping Chen; Yi Ju Tseng; Kai Ping Hsu; Sheau Ling Hsieh; Yin Hsiu Chien; Wuh Liang Hwu; Feipei Lai

doi:10.1109/ASONAM.2012.145

Newborn screening for phenylketonuria: Machine learning vs clinicians

Wei Hsin Chen^*, Han Ping Chen, Yi Ju Tseng, Kai Ping Hsu, Sheau Ling Hsieh, Yin Hsiu Chien, Wuh Liang Hwu, Feipei Lai

^*Corresponding author for this work

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

4 Scopus citations

Abstract

The metabolic disorders may hinder an infant's normal physical or mental development during the neonatal period. The metabolic diseases can be treated by effective therapies if the diseases are discovered in the early stages. Therefore, newborn screening program is essential to prevent neonatal from these damages. In the paper, a support vector machine (SVM) based algorithm is introduced in place of cut-off value decision to evaluate the analyte elevation raw data associated with Phenylketonuria. The data were obtained from tandem mass spectrometry (MS/MS) for newborns. In addition, a combined feature selection mechanism is proposed to compare with the cut-off scheme. By adapting the mechanism, the number of suspected cases is reduced substantially; it also handles the medical resources effectively and efficiently.

Original language	English
Title of host publication	Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
Pages	798-803
Number of pages	6
DOIs	https://doi.org/10.1109/ASONAM.2012.145
State	Published - 2012
Externally published	Yes
Event	2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 - Istanbul, Turkey Duration: 26 08 2012 → 29 08 2012

Publication series

Name	Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012

Conference

Conference	2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
Country/Territory	Turkey
City	Istanbul
Period	26/08/12 → 29/08/12

Keywords

Newborn screening
Support vector machine
Tandem mass spectrometry

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10.1109/ASONAM.2012.145

Cite this

Chen, W. H., Chen, H. P., Tseng, Y. J., Hsu, K. P., Hsieh, S. L., Chien, Y. H., Hwu, W. L., & Lai, F. (2012). Newborn screening for phenylketonuria: Machine learning vs clinicians. In Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 (pp. 798-803). Article 6425662 (Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012). https://doi.org/10.1109/ASONAM.2012.145

Chen, Wei Hsin ; Chen, Han Ping ; Tseng, Yi Ju et al. / Newborn screening for phenylketonuria : Machine learning vs clinicians. Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012. 2012. pp. 798-803 (Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012).

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title = "Newborn screening for phenylketonuria: Machine learning vs clinicians",

abstract = "The metabolic disorders may hinder an infant's normal physical or mental development during the neonatal period. The metabolic diseases can be treated by effective therapies if the diseases are discovered in the early stages. Therefore, newborn screening program is essential to prevent neonatal from these damages. In the paper, a support vector machine (SVM) based algorithm is introduced in place of cut-off value decision to evaluate the analyte elevation raw data associated with Phenylketonuria. The data were obtained from tandem mass spectrometry (MS/MS) for newborns. In addition, a combined feature selection mechanism is proposed to compare with the cut-off scheme. By adapting the mechanism, the number of suspected cases is reduced substantially; it also handles the medical resources effectively and efficiently.",

keywords = "Newborn screening, Support vector machine, Tandem mass spectrometry",

author = "Chen, {Wei Hsin} and Chen, {Han Ping} and Tseng, {Yi Ju} and Hsu, {Kai Ping} and Hsieh, {Sheau Ling} and Chien, {Yin Hsiu} and Hwu, {Wuh Liang} and Feipei Lai",

year = "2012",

doi = "10.1109/ASONAM.2012.145",

language = "英语",

isbn = "9780769547992",

series = "Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012",

pages = "798--803",

booktitle = "Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012",

note = "2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 ; Conference date: 26-08-2012 Through 29-08-2012",

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Chen, WH, Chen, HP, Tseng, YJ, Hsu, KP, Hsieh, SL, Chien, YH, Hwu, WL & Lai, F 2012, Newborn screening for phenylketonuria: Machine learning vs clinicians. in Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012., 6425662, Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012, pp. 798-803, 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012, Istanbul, Turkey, 26/08/12. https://doi.org/10.1109/ASONAM.2012.145

Newborn screening for phenylketonuria: Machine learning vs clinicians. / Chen, Wei Hsin; Chen, Han Ping; Tseng, Yi Ju et al.
Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012. 2012. p. 798-803 6425662 (Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012).

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

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AU - Hsieh, Sheau Ling

AU - Chien, Yin Hsiu

AU - Hwu, Wuh Liang

AU - Lai, Feipei

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Chen WH, Chen HP, Tseng YJ, Hsu KP, Hsieh SL, Chien YH et al. Newborn screening for phenylketonuria: Machine learning vs clinicians. In Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012. 2012. p. 798-803. 6425662. (Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012). doi: 10.1109/ASONAM.2012.145

Newborn screening for phenylketonuria: Machine learning vs clinicians

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Keywords

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