Health Insurance Fraud Detection Experiments
Listing Websites about Health Insurance Fraud Detection Experiments
Healthcare insurance fraud detection using data mining
(2 days ago) WebAnother experiment retrieved frequent rules using association rule mining with apriori algorithm combined with unsupervised techniques in 868.18 seconds. Outlier-based Health Insurance Fraud Detection for US Medicaid Data. In: ICEIS (2). 2014. p. …
https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-024-02512-4
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Health insurance fraud detection based on multi-channel …
(7 days ago) WebRecent heterogeneous graph-based approaches to health insurance fraud detection have been limited by a number of challenges. These methods focus on …
https://www.sciencedirect.com/science/article/pii/S2405844024060766
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Health insurance fraud detection by using an attributed …
(2 days ago) WebHealth insurance fraud detection problem with an AHIN. The health insurance fraud detection problem can be defined by modelling different objects and …
https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-023-02152-0
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Healthcare insurance fraud detection using data mining
(8 days ago) Webthe frauds in healthcare insurance system. Fraud can be identied through the services availing as well as provid-ing patterns. Availing patterns such as repetition of ser-vices, …
https://link.springer.com/content/pdf/10.1186/s12911-024-02512-4.pdf
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Blockchain and AI-Empowered Healthcare Insurance Fraud …
(5 days ago) WebMotivated by these facts, we present a systematic survey for Artificial Intelligence (AI) and blockchain-enabled secure health insurance fraud detection in …
https://ieeexplore.ieee.org/document/9843995/
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Healthcare insurance fraud detection using data mining
(1 days ago) WebMethodolgy: In this study, a fraud detection methodology is presented that utilizes association rule mining augmented with unsupervised learning techniques to …
https://pubmed.ncbi.nlm.nih.gov/38671513/
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Health insurance fraud detection based on multi-channel …
(2 days ago) WebHealth insurance fraud is becoming more common and impacting the fairness and sustainability of the health insurance system. Traditional health insurance fraud …
https://ui.adsabs.harvard.edu/abs/2024Heliy..1030045H/abstract
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WMTDBC: An unsupervised multivariate analysis model for fraud …
(7 days ago) WebAn unsupervised multivariate analysis for health insurance fraud detection. The unsupervised model developed in this study has two stages: The first stage …
https://www.sciencedirect.com/science/article/pii/S0957417422022771
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Health insurance fraud detection by using an attributed
(8 days ago) WebHealth insurance fraud detection Health insurance fraud has a signicant impact on healthcare and daily life. Early research on fraud detec-tion focused on a rule …
https://link.springer.com/content/pdf/10.1186/s12911-023-02152-0.pdf
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Feature engineering to detect fraud using healthcare claims data
(7 days ago) WebData mining and machine learning technologies have been widely used for fraud detection in various domains such as auto-insurance, life-insurance, health …
https://www.sciencedirect.com/science/article/pii/S0957417422015330
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Health insurance fraud detection by using an attributed - PubMed
(1 days ago) WebTraditional fraud detection methods have tended to focus on the attributes of a single visit and have ignored the behavioural relationships of multiple visits by patients. …
https://pubmed.ncbi.nlm.nih.gov/37024897/
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Data-Centric AI for Healthcare Fraud Detection - PMC
(4 days ago) WebThis study presents a data-centric approach to improving healthcare fraud classification rates within the U.S. Medicare program. The U.S. Medicare program …
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10173919/
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Explainable machine learning models for Medicare fraud detection
(7 days ago) WebAs a means of building explainable machine learning models for Big Data, we apply a novel ensemble supervised feature selection technique. The technique is applied …
https://journalofbigdata.springeropen.com/articles/10.1186/s40537-023-00821-5
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Healthcare insurance fraud detection using data mining - PMC
(4 days ago) WebAnother experiment retrieved frequent rules using association rule mining with apriori algorithm combined with unsupervised techniques in 868.18 seconds.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11046758/
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Health insurance fraud detection by using an attributed …
(4 days ago) WebHealth insurance fraud detection problem with an AHIN. The health insurance fraud detection problem can be defined by modelling different objects and …
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10080767/
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A Systematic Review and Qualitative Assessment of Fraud …
(6 days ago) WebApplying a previously validated approach that has not been taken by prior health care fraud reviews, our qualitative method showed high validity in terms of …
https://www.tandfonline.com/doi/full/10.1080/10920277.2021.1895843
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Bagging Vs. Boosting in Ensemble Machine Learning? An …
(6 days ago) WebFor instance, in the study of (Guoming et al. Citation 2022), they put out a model for identifying health insurance fraud relying on the consortium blockchain and the …
https://www.tandfonline.com/doi/full/10.1080/08839514.2024.2355024
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Network analytics for insurance fraud detection: a critical case …
(Just Now) WebHowever, the literature on fraud detection using NA in insurance is still scarce. This paper adds to that literature in four ways: 1. Multiple state-of-the-art NA …
https://link.springer.com/article/10.1007/s13385-024-00384-6
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Medical Insurance Fraud Detection using Graph Neural …
(6 days ago) Webfound that health care fraud loss rates ranged from 3.29% - 10.0% (5.59% on average), and health care fraud rates ranged from 0.47% - 7.1% (4.23% on average). Annual …
https://bit.kuas.edu.tw/~jni/2022/vol7/s2/14.JNI0311.pdf
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Seamless Collaboration & Fraud Detection Create Powerful …
(2 days ago) WebMay 20th 2024. The battle against fraudulent claims is a constant challenge. However, a powerful partnership combining seamless collaboration with cutting-edge …
https://davies-group.com/northamerica/knowledge/insurancefrauddetection/
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Julio Pernía Aznar: Revolutionising Car Insurance Cash Settlements …
(9 days ago) WebThe implementation of AI in fraud detection has led to impressive results. For example, the insurance industry has seen a significant reduction in fraudulent activities, …
https://insurtechdigital.com/articles/insurance-cash-settlements-ready-for-an-ai-overhaul
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How to detect healthcare fraud? “A systematic review”
(7 days ago) WebIn addition, the processed data sets are regarded as big Data and as such, for their fraud detection experiments use the Spark above the Hadoop YARN cluster that …
https://www.sciencedirect.com/science/article/pii/S0213911121002661
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Health insurance fraud detection based on multi-channel …
(8 days ago) WebExperiments have shown that multi-channel heterogeneous graph structure learning in MHGSL can be very helpful for health insurance fraud detection. It provides a …
https://www.cell.com/heliyon/pdf/S2405-8440(24)06076-6.pdf
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Unraveling Healthcare Fraud: Exploring ROI and Deterrence …
(2 days ago) WebIn the ongoing battle against healthcare fraud, understanding the effectiveness of anti-fraud efforts is paramount. This Q&A, featuring Questrom Assistant Professor of …
https://insights.bu.edu/unraveling-healthcare-fraud-exploring-roi-and-deterrence-challenges/
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Fraud, Waste and Abuse (FWA) - HCP
(8 days ago) WebFalse Claims Act. The False Claims Act (FCA) is a federal statute that is intended to prevent healthcare fraud and recover losses involving any federally funded contract or program, …
https://www.healthcarepartnersny.com/wp-content/uploads/2020/08/FWA-Provider-Training_Aug-2020.pdf
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Corporate Fraud Handbook - Wiley Online Library
(9 days ago) WebTo detail a classification system to explain the various schemes used by executives, owners, managers, and employees to commit these offenses. To quantify the losses from these …
https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781119351962.fmatter
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Financial Statement Fraud - Wiley Online Library
(9 days ago) WebFinancial statement fraud : strategies for detection and investigation / Gerard M. Zack. p. cm. Includes bibliographical references and index. ISBN 978-1-118-30155-5 (cloth); …
https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781118527436.fmatter
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