A graph-based contrastive learning framework for medicare insurance fraud detection

Song XIAO, Ting BAI, Xiangchong CUI, Bin WU, Xinkai MENG, Bai WANG

Front. Comput. Sci. ›› 2023, Vol. 17 ›› Issue (2) : 172341.

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Front. Comput. Sci. ›› 2023, Vol. 17 ›› Issue (2) : 172341. DOI: 10.1007/s11704-022-1734-0
Artificial Intelligence
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A graph-based contrastive learning framework for medicare insurance fraud detection

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Song XIAO, Ting BAI, Xiangchong CUI, Bin WU, Xinkai MENG, Bai WANG. A graph-based contrastive learning framework for medicare insurance fraud detection. Front. Comput. Sci., 2023, 17(2): 172341 https://doi.org/10.1007/s11704-022-1734-0

References

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Guo J, Liu G N, Zuo Y, Wu J J. Learning sequential behavior representations for fraud detection. In: Proceedings of 2018 IEEE International Conference on Data Mining. 2018, 127−136
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Cao L H, Qin F L, Yan Z M. TLSTM-based medical insurance fraud detection. Computer Engineering and Applications, 2020, 56(21): 237-241
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Li Q T, Xu Y . VS-GRU: a variable sensitive gated recurrent neural network for multivariate time series with massive missing values. Applied Sciences, 2019, 9( 15): 3041

Acknowledgements

This work was supported by the National Key Research and Development Program of China (No. 2018YFC0831500) and the National Natural Science Foundation of China (Grant No. 61972047).

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