This paper is in the following e-collection/theme issue:

Theme issue 2019: Health Natural Language Processing (17) Electronic Health Records (1053) Natural Language Processing (693) Secondary Use of Clinical Data for Research and Surveillance (367)

Published on in Vol 8, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17653, first published .
Medical Knowledge Graph to Enhance Fraud, Waste, and Abuse Detection on Claim Data: Model Development and Performance Evaluation

Medical Knowledge Graph to Enhance Fraud, Waste, and Abuse Detection on Claim Data: Model Development and Performance Evaluation

Medical Knowledge Graph to Enhance Fraud, Waste, and Abuse Detection on Claim Data: Model Development and Performance Evaluation

Authors of this article:

Haixia Sun1 Author Orcid Image ;   Jin Xiao2 Author Orcid Image ;   Wei Zhu2 Author Orcid Image ;   Yilong He2 Author Orcid Image ;   Sheng Zhang2 Author Orcid Image ;   Xiaowei Xu1 Author Orcid Image ;   Li Hou1 Author Orcid Image ;   Jiao Li1 Author Orcid Image ;   Yuan Ni2 Author Orcid Image ;   Guotong Xie2 Author Orcid Image
Article Authors Cited by (18) Tweetations (1) Metrics

Haixia Sun   1 * , MSc ;   Jin Xiao   2 * , MSc ;   Wei Zhu   2 , MSc ;   Yilong He   2 , MSc ;   Sheng Zhang   2 , MSc ;   Xiaowei Xu   1 , MSc ;   Li Hou   1 , PhD ;   Jiao Li   1 * , PhD ;   Yuan Ni   2 , PhD ;   Guotong Xie   2 * , PhD

1 Institute of Medical Information & Library, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China

2 PingAn Health Technology, Shenzhen, China

*these authors contributed equally

Corresponding Author:

  • Guotong Xie, PhD
  • PingAn Health Technology
  • Qianhai Complex A201, Qianwan Road 1
  • Qianhai Shenzhen-Hong Kong Cooperation Zone
  • Shenzhen
  • China
  • Phone: 86 21-38649320
  • Email: xieguotong@pingan.com.cn