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A graph-based contrastive learning framework for medicare insurance fraud detection 被引量:1

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摘要 1 Introduction With the improvement of people's living standards,medical insurance has gradually moved towards universal coverage in recent years.Nevertheless,problems such asmedical insurance fraud,resource waste and drug abuse emerge successively,which cause a colossal waste of public resources.Therefore,reducing or eliminating medical insurance fraud can safeguard the medical insurance fund,which is essential for promoting economic development,improving public health,and maintaining social stability[1].The specialized challenges for medical insurance fraud detection are summarized as follows.
出处 《Frontiers of Computer Science》 SCIE EI CSCD 2023年第2期245-247,共3页 中国计算机科学前沿(英文版)
基金 supported by the National Key Research and Development Program of China(No.2018YFC0831500) the National Natural Science Foundation of China(Grant No.61972047).
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