Enriching Health Care Fraud Detection System Using ANN
Abstract & Details
Research Area
Computer Engineering
Keywords
Data labels
Data vector
Preprocessing
Protocol collection
K-means Clustering
ANN
Fuzzy Classification
probability
Fraud Estimation
Fraud claim identification
Insurance
Algorithm design and analysis
Drugs (Medicines)
Abstract
Unavailability of a medical fraud detector encourages the rate of fraud in the healthcare insurance sector to increase by a great extent such that the medical practicians delude the insurance holders very well. Consequently, in order to do away with these fraudulent insurance claims, a system that discovers the fake claims and facilitates in scaling down the rate of insurance claim frauds is essential. Several techniques like Social Network Analysis (SNA), Duplicate and Gap testing, Spike Analysis, Social Customer Relationship Management (SCRM) and Predictive Modelling are utilized in order to attain a system owning to a successful fraud detection process. But, on the contrary, these systems face troubles of a large time and space complexities. To enhance the process of fraud claims detection of the doctors at the insurance company’s end the proposed method puts forwards an idea of identifying fraud claims by clustering the claims based on the protocols by using the K-means clustering technique which is then powered with ANN to extract the fraud list and this process is supported by fuzzy logic classification hypothesis.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Aditi Kamath | Modern Education Society's College Of Engineering |
| 2 | Darshana Akadkar | Modern Education Society's College Of Engineering |
| 3 | Pooja Divase | Modern Education Society's College Of Engineering |
| 4 | Shraddha Hundalekar | Modern Education Society's College Of Engineering |
| 5 | N.I.Ujloomwale | Modern Education Society's College Of Engineering |
How to Cite
Use the following formats to cite this article in your research.
APA Style
Kamath, Aditi, Akadkar, Darshana, Divase, Pooja, Hundalekar, Shraddha, & N.I.Ujloomwale (2018). Enriching Health Care Fraud Detection System Using ANN. International Journal of Advance Research and Innovative Ideas In Education, 4(3), 1756-1763.
MLA Style
Kamath, Aditi, et al. "Enriching Health Care Fraud Detection System Using ANN." International Journal of Advance Research and Innovative Ideas In Education, vol. 4, no. 3, 2018, pp. 1756-1763.
IEEE Style
Aditi Kamath, Darshana Akadkar, Pooja Divase, Shraddha Hundalekar, and N.I.Ujloomwale, "Enriching Health Care Fraud Detection System Using ANN," International Journal of Advance Research and Innovative Ideas In Education, vol. 4, no. 3, pp. 1756-1763, 2018.
Vancouver Style
Kamath Aditi, Akadkar Darshana, Divase Pooja, Hundalekar Shraddha, N.I.Ujloomwale. Enriching Health Care Fraud Detection System Using ANN. International Journal of Advance Research and Innovative Ideas In Education. 2018;4(3):1756-1763.
Harvard Style
Kamath, Aditi, Akadkar, Darshana, Divase, Pooja, Hundalekar, Shraddha, & N.I.Ujloomwale (2018) 'Enriching Health Care Fraud Detection System Using ANN', International Journal of Advance Research and Innovative Ideas In Education, 4(3), pp. 1756-1763.
Chicago Style
Kamath, Aditi, et al. "Enriching Health Care Fraud Detection System Using ANN." International Journal of Advance Research and Innovative Ideas In Education 4, no. 3 (2018): 1756-1763.
Turabian Style
Kamath, Aditi, et al. "Enriching Health Care Fraud Detection System Using ANN." International Journal of Advance Research and Innovative Ideas In Education 4, no. 3 (2018): 1756-1763.
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