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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Detalles Bibliográficos
Autores principales: Massi, Michela Carlotta, Ieva, Francesca, Lettieri, Emanuele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Technical Advance
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7362640/
https://www.ncbi.nlm.nih.gov/pubmed/32664923
http://dx.doi.org/10.1186/s12911-020-01143-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7362640/
https://www.ncbi.nlm.nih.gov/pubmed/32664923
http://dx.doi.org/10.1186/s12911-020-01143-9

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