• 综合
  • 标题
  • 关键词
  • 摘要
  • 学者
  • 期刊-刊名
  • 期刊-ISSN
  • 会议名称
搜索

作者:

Akhtar, Faheem (Akhtar, Faheem.) | Li, Jianqiang (Li, Jianqiang.) (学者:李建强) | Yan, Pei (Yan, Pei.) | Imran, Azhar (Imran, Azhar.) | Muhammad Shaikh, Gul (Muhammad Shaikh, Gul.) | Xu, Chun (Xu, Chun.)

收录:

CPCI-S EI

摘要:

Large for gestational (LGA) means the fetus having an abnormal birth weight. It adheres severe complications during and after the maternal period. Therefore, this research presents an ensemble classification scheme using Chinese National Pre-Pregnancy Examination Program dataset to classify a fetus as an LGA or non-LGA based on provided Chinese LGA classification guidelines. Moreover, the proposed scheme is comprised of data cleansing and ensemble classification schemes that have drastically improved the LGA classification process with improved performance results compared to present published studies. Therefore, the recommended scheme can be utilized by healthcare professionals to build an enhanced and reliable LGA classification system. © 2020 IEEE.

关键词:

Application programs Classification (of information)

作者机构:

  • [ 1 ] [Akhtar, Faheem]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Akhtar, Faheem]Department of Computer Science, Sukkur Iba University, Sukkur; 65200, Pakistan
  • [ 3 ] [Li, Jianqiang]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Yan, Pei]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Imran, Azhar]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 6 ] [Muhammad Shaikh, Gul]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 7 ] [Xu, Chun]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China

通讯作者信息:

电子邮件地址:

查看成果更多字段

相关关键词:

来源 :

年份: 2020

页码: 1455-1459

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

万方被引频次:

中文被引频次:

近30日浏览量: 2

归属院系:

在线人数/总访问数:623/2895803
地址:北京工业大学图书馆(北京市朝阳区平乐园100号 邮编:100124) 联系我们:010-67392185
版权所有:北京工业大学图书馆 站点建设与维护:北京爱琴海乐之技术有限公司