Construction of a prediction model for nephropathy among obese patients using genetic and clinical features

Guan Mau Huang; Yi Cheng Chen; Julia Tzu Ya Weng

doi:10.1007/978-3-319-25660-3_9

Construction of a prediction model for nephropathy among obese patients using genetic and clinical features

Guan Mau Huang, Yi Cheng Chen, Julia Tzu Ya Weng

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

摘要

Obesity is a complex disease arising from an excessive accumulation of body fat which leads to various complications such as diabetes, hypertension, and renal diseases. The growing prevalence of obesity is also becoming a major risk factor for nephropathy. When patients are diagnosed with nephropathy, their progression towards renal failure is usually inevitable. Therefore, a prediction tool will help medical doctors identify patients with a higher risk of developing nephropathy and implement early treatment or prevention. In this study, we attempted to construct a diagnostic support system for nephropathy using clinical and genetic traits. Our results show that prediction models involving the use of both genetic and clinical features yielded the best classification performance. Our finding is in accordance with the complex nature of obesity-related nephropathy and support the notion of using genetic traits to design a personalized diagnostic model.

原文	???core.languages.en_GB???
主出版物標題	Trends and Applications in Knowledge Discovery and Data Mining, PAKDD 2015 Workshops
主出版物子標題	BigPMA, VLSP, QIMIE, DAEBH, Revised Selected Papers
編輯	Xiao-Li Li, David Cheung, Ee-Peng Lim, Hiroshi Motoda, Tu-Bao Ho, Tru Cao, Zhi-Hua Zhou
發行者	Springer Verlag
頁面	104-112
頁數	9
ISBN（列印）	9783319256597
DOIs	https://doi.org/10.1007/978-3-319-25660-3_9
出版狀態	已出版 - 2015
事件	19th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2015 - Ho Chi Minh City, Viet Nam 持續時間: 19 5月 2015 → 19 5月 2015

出版系列

名字	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	9441
ISSN（列印）	0302-9743
ISSN（電子）	1611-3349

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???event.eventtypes.event.conference???	19th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2015
國家/地區	Viet Nam
城市	Ho Chi Minh City
期間	19/05/15 → 19/05/15

UN SDG

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10.1007/978-3-319-25660-3_9

引用此

Huang, G. M., Chen, Y. C., & Weng, J. T. Y. (2015). Construction of a prediction model for nephropathy among obese patients using genetic and clinical features. 於 X-L. Li, D. Cheung, E-P. Lim, H. Motoda, T-B. Ho, T. Cao, & Z-H. Zhou (編輯), Trends and Applications in Knowledge Discovery and Data Mining, PAKDD 2015 Workshops: BigPMA, VLSP, QIMIE, DAEBH, Revised Selected Papers (頁 104-112). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 9441). Springer Verlag. https://doi.org/10.1007/978-3-319-25660-3_9

Huang, Guan Mau ; Chen, Yi Cheng ; Weng, Julia Tzu Ya. / Construction of a prediction model for nephropathy among obese patients using genetic and clinical features. Trends and Applications in Knowledge Discovery and Data Mining, PAKDD 2015 Workshops: BigPMA, VLSP, QIMIE, DAEBH, Revised Selected Papers. 編輯 / Xiao-Li Li ; David Cheung ; Ee-Peng Lim ; Hiroshi Motoda ; Tu-Bao Ho ; Tru Cao ; Zhi-Hua Zhou. Springer Verlag, 2015. 頁 104-112 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Obesity is a complex disease arising from an excessive accumulation of body fat which leads to various complications such as diabetes, hypertension, and renal diseases. The growing prevalence of obesity is also becoming a major risk factor for nephropathy. When patients are diagnosed with nephropathy, their progression towards renal failure is usually inevitable. Therefore, a prediction tool will help medical doctors identify patients with a higher risk of developing nephropathy and implement early treatment or prevention. In this study, we attempted to construct a diagnostic support system for nephropathy using clinical and genetic traits. Our results show that prediction models involving the use of both genetic and clinical features yielded the best classification performance. Our finding is in accordance with the complex nature of obesity-related nephropathy and support the notion of using genetic traits to design a personalized diagnostic model.",

keywords = "Nephropathy, Obesity, Personalized diagnostic support system, Prediction",

author = "Huang, {Guan Mau} and Chen, {Yi Cheng} and Weng, {Julia Tzu Ya}",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2015 ; Conference date: 19-05-2015 Through 19-05-2015",

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Huang, GM, Chen, YC & Weng, JTY 2015, Construction of a prediction model for nephropathy among obese patients using genetic and clinical features. 於 X-L Li, D Cheung, E-P Lim, H Motoda, T-B Ho, T Cao & Z-H Zhou (編輯), Trends and Applications in Knowledge Discovery and Data Mining, PAKDD 2015 Workshops: BigPMA, VLSP, QIMIE, DAEBH, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 9441, Springer Verlag, 頁 104-112, 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2015, Ho Chi Minh City, Viet Nam, 19/05/15. https://doi.org/10.1007/978-3-319-25660-3_9

Construction of a prediction model for nephropathy among obese patients using genetic and clinical features. / Huang, Guan Mau; Chen, Yi Cheng; Weng, Julia Tzu Ya.
Trends and Applications in Knowledge Discovery and Data Mining, PAKDD 2015 Workshops: BigPMA, VLSP, QIMIE, DAEBH, Revised Selected Papers. 編輯 / Xiao-Li Li; David Cheung; Ee-Peng Lim; Hiroshi Motoda; Tu-Bao Ho; Tru Cao; Zhi-Hua Zhou. Springer Verlag, 2015. p. 104-112 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 9441).

研究成果: 書貢獻/報告類型 › 會議論文篇章 › 同行評審

TY - GEN

T1 - Construction of a prediction model for nephropathy among obese patients using genetic and clinical features

AU - Huang, Guan Mau

AU - Chen, Yi Cheng

AU - Weng, Julia Tzu Ya

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - Obesity is a complex disease arising from an excessive accumulation of body fat which leads to various complications such as diabetes, hypertension, and renal diseases. The growing prevalence of obesity is also becoming a major risk factor for nephropathy. When patients are diagnosed with nephropathy, their progression towards renal failure is usually inevitable. Therefore, a prediction tool will help medical doctors identify patients with a higher risk of developing nephropathy and implement early treatment or prevention. In this study, we attempted to construct a diagnostic support system for nephropathy using clinical and genetic traits. Our results show that prediction models involving the use of both genetic and clinical features yielded the best classification performance. Our finding is in accordance with the complex nature of obesity-related nephropathy and support the notion of using genetic traits to design a personalized diagnostic model.

AB - Obesity is a complex disease arising from an excessive accumulation of body fat which leads to various complications such as diabetes, hypertension, and renal diseases. The growing prevalence of obesity is also becoming a major risk factor for nephropathy. When patients are diagnosed with nephropathy, their progression towards renal failure is usually inevitable. Therefore, a prediction tool will help medical doctors identify patients with a higher risk of developing nephropathy and implement early treatment or prevention. In this study, we attempted to construct a diagnostic support system for nephropathy using clinical and genetic traits. Our results show that prediction models involving the use of both genetic and clinical features yielded the best classification performance. Our finding is in accordance with the complex nature of obesity-related nephropathy and support the notion of using genetic traits to design a personalized diagnostic model.

KW - Nephropathy

KW - Obesity

KW - Personalized diagnostic support system

KW - Prediction

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SN - 9783319256597

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 104

EP - 112

BT - Trends and Applications in Knowledge Discovery and Data Mining, PAKDD 2015 Workshops

A2 - Li, Xiao-Li

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A2 - Lim, Ee-Peng

A2 - Motoda, Hiroshi

A2 - Ho, Tu-Bao

A2 - Cao, Tru

A2 - Zhou, Zhi-Hua

PB - Springer Verlag

T2 - 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2015

Y2 - 19 May 2015 through 19 May 2015

ER -

Huang GM, Chen YC, Weng JTY. Construction of a prediction model for nephropathy among obese patients using genetic and clinical features. 於 Li X-L, Cheung D, Lim E-P, Motoda H, Ho T-B, Cao T, Zhou Z-H, 編輯, Trends and Applications in Knowledge Discovery and Data Mining, PAKDD 2015 Workshops: BigPMA, VLSP, QIMIE, DAEBH, Revised Selected Papers. Springer Verlag. 2015. p. 104-112. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-25660-3_9

Construction of a prediction model for nephropathy among obese patients using genetic and clinical features

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