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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...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2018
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| Materias: | |
| 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 |