A Fraud Resilient Medical Insurance Claim System
Abstract
As many countries in the world start to experience population aging, there are an increasing number of people relying on medical insurance to access healthcare resources. Medical insurance frauds are causing billions of dollars in losses for public healthcare funds. The detection of medical insurance frauds is an important and difficult challenge for the artificial intelligence (AI) research community. This paper outlines HFDA, a hybrid AI approach to effectively and efficiently identify fraudulent medical insurance claims which has been tested in an online medical insurance claim system in China.
Cite
Text
Shi et al. "A Fraud Resilient Medical Insurance Claim System." AAAI Conference on Artificial Intelligence, 2016. doi:10.1609/AAAI.V30I1.9825Markdown
[Shi et al. "A Fraud Resilient Medical Insurance Claim System." AAAI Conference on Artificial Intelligence, 2016.](https://mlanthology.org/aaai/2016/shi2016aaai-fraud/) doi:10.1609/AAAI.V30I1.9825BibTeX
@inproceedings{shi2016aaai-fraud,
title = {{A Fraud Resilient Medical Insurance Claim System}},
author = {Shi, Yuliang and Sun, Chenfei and Li, Qingzhong and Cui, Lizhen and Yu, Han and Miao, Chunyan},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2016},
pages = {4393-4394},
doi = {10.1609/AAAI.V30I1.9825},
url = {https://mlanthology.org/aaai/2016/shi2016aaai-fraud/}
}