Data mining application to healthcare fraud detection: a two-step unsupervised clustering method for outlier detection with administrative databases

Volume: 20, Issue: 1
Published: Jul 14, 2020
Abstract
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 developing a novel data mining model devoted to fraud detection among hospitals using Hospital Discharge Charts (HDC) in Administrative Databases. In...
Paper Details
Title
Data mining application to healthcare fraud detection: a two-step unsupervised clustering method for outlier detection with administrative databases
Published Date
Jul 14, 2020
Volume
20
Issue
1
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