Recent findings from the University of Louisiana Lafayette offer new insights into insurance (identifying health insurance claims fraud using a mix of clinical concepts): Insurance – InsuranceNewsNet

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2022 Sep 09 (NewsRx) — By a News Reporter – Staff News Editor at Health policy and daily law — New research on insurance is reported. According to reports from Lafayette, Louisiana, by NewsRx correspondents, the research said, “Patients rely on health insurance provided by government systems, private systems, or both to utilize costly health care expenditures. This reliance on health insurance drives some health service providers to commit insurance fraud.

Our editors got a citation from the research of the University of Louisiana Lafayette“Although the number of such service providers is small, it is reported that insurers lose billions of dollars each year due to fraud. In this article, we formulate the problem of fraud detection on minimal claims data composed of medical diagnoses and procedure codes.We present a solution to the problem of detecting fraudulent claims using a novel representation learning approach, which translates diagnosis and procedure codes into mixtures We also investigate MCC extensions using long-short-term memory networks and robust principal component analysis.

According to the editors, the research concluded: “Our experimental results demonstrate promising results in identifying fraudulent registrations.”

This research has been peer reviewed.

For more information on this research, see: Identifying Health Insurance Claims Fraud Using a Blend of Clinical Concepts. IEEE Transactions on Services Computing2022;15(4):1-1. IEEE Transactions on Services Computing can be contacted at: Ieee Computer Soc, 10662 Circle Los VaquerosBox 3014, Los Alamitos, California 90720-1314, UNITED STATES. (Institute of Electrical and Electronic Engineers – http://www.ieee.org/; IEEE Transactions on Services Computing – http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4629386)

News editors report that additional information can be obtained by contacting Md Enamel Haque, University of Louisiana Lafayette, School of Computing and Information, Lafayette, LA 70503, United States.

The direct object identifier (DOI) for this additional information is: https://doi.org/10.1109/tsc.2021.3051165. This DOI is a link to a free or paid online electronic document, and can be your direct source for a journal article and its citation.

(Our reports provide factual information on research and discoveries around the world.)

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