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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...
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| Опубликовано в: : | Daru |
|---|---|
| Главные авторы: | , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Springer International Publishing
2018
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6279664/ https://ncbi.nlm.nih.gov/pubmed/30460618 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s40199-018-0227-z |
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