Detecting medical prescriptions suspected of fraud using an unsupervised data mining algorithm

Nowadays, health insurance companies face various types of fraud, like phantom billing, up-coding, and identity theft. Detecting such frauds is thus of vital importance to reduce and eliminate corresponding financial losses. We used an unsupervised data mining algorithm and implemented an outlier de...

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Detalles Bibliográficos
Autores principales: Haddad Soleymani, Mohammad, Yaseri, Mehdi, Farzadfar, Farshad, Mohammadpour, Adel, Sharifi, Farshad, Kabir, Mohammad Javad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6279664/
https://www.ncbi.nlm.nih.gov/pubmed/30460618
http://dx.doi.org/10.1007/s40199-018-0227-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6279664/
https://www.ncbi.nlm.nih.gov/pubmed/30460618
http://dx.doi.org/10.1007/s40199-018-0227-z

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