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Data mining application to healthcare fraud detection: a two-step unsupervised clustering method for outlier detection with administrative databases
BACKGROUND: The healthcare sector is an interesting target for fraudsters. The availability of a great amount of data makes it possible to tackle this issue with the adoption of data mining techniques, making the auditing process more efficient and effective. This research has the objective of devel...
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| Pubblicato in: | BMC Med Inform Decis Mak |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
BioMed Central
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7362640/ https://ncbi.nlm.nih.gov/pubmed/32664923 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12911-020-01143-9 |
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