to download project abstract

The healthcare industry is a complex system and it is expanding at a rapid pace. At the same time fraud in this industry is turning into a critical problem. One of the issues is the misuse of the medical insurance systems. Machine learning and data mining techniques are used for automatically detecting the healthcare frauds. In this paper, we attempt to give a review on frauds in healthcare industry and the techniques for detecting such frauds. With an emphasis on the techniques used, determining the significant sources and the features of the healthcare data we proposed a machine learning model to tackle the issues related to the health insurance claims. The univariate and bivariate analysis are applied on the data to know the features pattern and then proper visualization of data to know which feature affects the most and a machine learning model is built on the pre-processed data.

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