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作者:

Mo, Haowen (Mo, Haowen.) | Li, Jianqiang (Li, Jianqiang.) (学者:李建强) | Chen, Shi (Chen, Shi.) | Pan, Hui (Pan, Hui.) | Yang, Ji-Jiang (Yang, Ji-Jiang.) | Wang, Qing (Wang, Qing.) | Mao, Rui (Mao, Rui.)

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CPCI-S Scopus

摘要:

The medical diagnosis process can be interpreted as a decision making process, which doctors determine whether a person is suffering from a disease based on the medical examination. This process can also be computerized in order to present medical diagnostic procedures in an accurate, objective, rational, and fast way. This paper presents a detection model for small for gestational age (SGA) based on support vector machine (SVM). For this purpose, a dataset was adopted from pregnancy eugenic investigation to train the classification model. Then empirical experiments were conducted for SGA detection. The results indicate that support vector machine is considerably effective to detect SGA to help doctors make the final diagnosis.

关键词:

Small for gestational age Healthcare Classification Support vector machine

作者机构:

  • [ 1 ] [Mo, Haowen]Beijing Univ Technol, Sch Software Engn, Beijing, Peoples R China
  • [ 2 ] [Li, Jianqiang]Beijing Univ Technol, Sch Software Engn, Beijing, Peoples R China
  • [ 3 ] [Mo, Haowen]Shenzhen Key Lab Serv Comp & Applicat, Guangdong Key Lab Popular High Performance Comp, Shenzhen, Peoples R China
  • [ 4 ] [Li, Jianqiang]Shenzhen Key Lab Serv Comp & Applicat, Guangdong Key Lab Popular High Performance Comp, Shenzhen, Peoples R China
  • [ 5 ] [Mao, Rui]Shenzhen Key Lab Serv Comp & Applicat, Guangdong Key Lab Popular High Performance Comp, Shenzhen, Peoples R China
  • [ 6 ] [Chen, Shi]Beijing Union Med Coll Hosp, Dept Endocrinol, Beijing, Peoples R China
  • [ 7 ] [Pan, Hui]Beijing Union Med Coll Hosp, Dept Endocrinol, Beijing, Peoples R China
  • [ 8 ] [Yang, Ji-Jiang]Tsinghua Univ, Tsinghua Natl Lab Informat Sci & Technol, Beijing, Peoples R China
  • [ 9 ] [Wang, Qing]Tsinghua Univ, Tsinghua Natl Lab Informat Sci & Technol, Beijing, Peoples R China

通讯作者信息:

  • [Yang, Ji-Jiang]Tsinghua Univ, Tsinghua Natl Lab Informat Sci & Technol, Beijing, Peoples R China

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来源 :

INCLUSIVE SMART CITIES AND DIGITAL HEALTH

ISSN: 0302-9743

年份: 2016

卷: 9677

页码: 59-68

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 1

ESI高被引论文在榜: 0 展开所有

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