Automated Health Insurance Processing Framework with Intelligent Fraud Detection, Risk Classification and Premium Prediction
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s42979-024-02801-9.pdf
Reference27 articles.
1. Yang W, Zhang S. Research on bootstrapping algorithm for health insurance data fraud detection based on decision tree. In: 2021 7th IEEE international conference on big data security on cloud, 2021;57–62. https://doi.org/10.1109/BigDataSecurityHPSCIDS52275.2021.00021.G.
2. Healthcare provider fraud detection analysis dataset. https://www.kaggle.com/datasets/rohitrox/healthcare-provider-fraud-detection-analysis?select=Train_Inpatientdata-1542865627584.csv.
3. Kaddi S, Patil M. Ensemble learning based health care claim fraud detection in an imbalance data environment. Indones J Electr Eng Comput Sci. 2023;32:1686. https://doi.org/10.11591/ijeecs.v32.i3.pp1686-1694.
4. Sun C, Li Q, Li H, Shi Y, Zhang S, Guo W. Patient cluster divergence based healthcare insurance fraudster detection. IEEE Access. 2019;7:14162–70. https://doi.org/10.1109/ACCESS.2018.2886680.
5. Badriyah T, Rahmaniah L, Syarif I. Nearest neighbour and statistics method based for detecting fraud in auto insurance. In: ICAE, 2018;1–5.
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