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

資訊管理學系

研究成果: 書貢獻/報告類型 › 會議論文篇章 › 同行評審

3 引文斯高帕斯（Scopus）

摘要

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.

原文	???core.languages.en_GB???
主出版物標題	Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
頁面	798-803
頁數	6
DOIs	https://doi.org/10.1109/ASONAM.2012.145
出版狀態	已出版 - 2012
事件	2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 - Istanbul, Turkey 持續時間: 26 8月 2012 → 29 8月 2012

出版系列

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

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
國家/地區	Turkey
城市	Istanbul
期間	26/08/12 → 29/08/12

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10.1109/ASONAM.2012.145

引用此

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. 於 Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 (頁 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 等. / 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. 頁 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",

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

研究成果: 書貢獻/報告類型 › 會議論文篇章 › 同行評審

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AU - Chen, Wei Hsin

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AU - Hsu, Kai Ping

AU - Hsieh, Sheau Ling

AU - Chien, Yin Hsiu

AU - Hwu, Wuh Liang

AU - Lai, Feipei

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AB - 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.

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Chen WH, Chen HP, Tseng YJ, Hsu KP, Hsieh SL, Chien YH 等. Newborn screening for phenylketonuria: Machine learning vs clinicians. 於 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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