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Paper Title: A Heuristic Approach To Predict False Claims in Health Care Sectors
Authors Name: Komal Survase , Manisha Sangshetty , Rajani Waghire , Smita Pawar , P. B. Jawalkar
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Published Paper Id: IJNRD1705024
Published In: Volume 2 Issue 5, May-2017
Abstract: Due to happening of health care fraud there is huge loss for companies. To overcome this problem some systems need to implement to identify fraud. To detect health care fraud many systems uses synthesized datasets, data mining techniques and hybrid approach. There are many health care fraud detection systems are available i) Survey on Hybrid Approach for Fraud Detection in Health Insurance, ii) Data Mining for Fraud Detection, iii) A survey on statistical methods for health care fraud detection. Many systems related to health care fraud are having performance issues regarding detection of fraud, so this paper proposes an idea of health care fraud detection. To enhance the process of fraud claims detection of the doctors at the insurance company’s end proposed method put forwards an idea of identifying fraud claims by clustering the claims based on the protocols by using the C-means clustering technique which is then powered with Hidden markov model to extract the fraud list and this process is catalyzed by fuzzy logic classification theory.
Keywords: Protocol Collection,C Means Clustering, Hidden Markov Model, Fuzzy Classification.
Cite Article: "A Heuristic Approach To Predict False Claims in Health Care Sectors", International Journal of Novel Research and Development (, ISSN:2456-4184, Vol.2, Issue 5, page no.112-114, May-2017, Available :
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