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

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

Sun, Haixia; Xiao, Jin; Zhu, Wei; He, Yilong; Zhang, Sheng; Xu, Xiaowei; Hou, Li; Li, Jiao; Ni, Yuan; Xie, Guotong.

Afiliación

Sun H; Institute of Medical Information & Library, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Xiao J; PingAn Health Technology, Shenzhen, China.
Zhu W; PingAn Health Technology, Shenzhen, China.
He Y; PingAn Health Technology, Shenzhen, China.
Zhang S; PingAn Health Technology, Shenzhen, China.
Xu X; Institute of Medical Information & Library, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Hou L; Institute of Medical Information & Library, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Li J; Institute of Medical Information & Library, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Ni Y; PingAn Health Technology, Shenzhen, China.
Xie G; PingAn Health Technology, Shenzhen, China.

JMIR Med Inform ; 8(7): e17653, 2020 Jul 23.

Article en En | MEDLINE | ID: mdl-32706714

Palabras clave

FWA detection; medical knowledge graph

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: JMIR Med Inform Año: 2020 Tipo del documento: Article País de afiliación: China Pais de publicación: Canadá

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