2022
DOI: 10.1016/j.ymeth.2022.09.004
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A Novel Multi-view Bi-clustering method for identifying abnormal Co-occurrence medical visit behaviors

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Cited by 5 publications
(2 citation statements)
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“…Wu Haibo (2014) criticized the dual role of the government in managing and executing medical insurance funds, highlighting the resulting high pressure, low e ciency, and inadequate supervision under the current "o cial establishment, o cial management, and o cial supervision" model [5] . Finally, Fan et al (2020) identi ed the core paths of hospital fraud, attributing them to individuals, organizations, systems, and policies through a rigorous process of literature coding, analysis, comparison, classi cation, and integration [6] .The fraud methods in the special medical insurance sector have also undergone a transformation, evolving from explicit to increasingly covert forms [7] .…”
Section: Introductionmentioning
confidence: 99%
“…Wu Haibo (2014) criticized the dual role of the government in managing and executing medical insurance funds, highlighting the resulting high pressure, low e ciency, and inadequate supervision under the current "o cial establishment, o cial management, and o cial supervision" model [5] . Finally, Fan et al (2020) identi ed the core paths of hospital fraud, attributing them to individuals, organizations, systems, and policies through a rigorous process of literature coding, analysis, comparison, classi cation, and integration [6] .The fraud methods in the special medical insurance sector have also undergone a transformation, evolving from explicit to increasingly covert forms [7] .…”
Section: Introductionmentioning
confidence: 99%
“…As the number of medical insurance fraud incidents continues to increase [ 8 , 9 ], fraudulent methods continue to shift from the explicit to the implicit, and fraudulent behavior continues to evolve and remain hidden [ 10 ], posing new challenges to the supervision of medical insurance funds. Whistleblowing is the most common and effective method of detecting fraud [ 11 ].…”
mentioning
confidence: 99%