Building prediction models and discovering important factors of health insurance fraud using machine learning methods-Reference-Cited by-同舟云学术

Building prediction models and discovering important factors of health insurance fraud using machine learning methods

Published:2023-05-19 Issue:7 Volume:14 Page:9607-9619
ISSN:1868-5137
Container-title:Journal of Ambient Intelligence and Humanized Computing
language:en
Short-container-title:J Ambient Intell Human Comput

Author:

Nalluri Venkateswarlu,Chang Jing-Rong,Chen Long-Sheng^ORCID,Chen Jia-Chuan

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s12652-023-04633-6.pdf

Reference54 articles.

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3. Bach MP, Dumičić K, Žmuk B, Ćurlin T, Zoroja J (2018) “Internal fraud in a project-based organization: CHAID decision tree analysis. Procedia Comput Sci 138:680–687

4. Bauder RA and Khoshgoftaar TM (2018) The detection of medicare fraud using machine learning methods with excluded provider labels. In: The Thirty-First International Florida Artificial Intelligence Research Society Conference, pp 404–409

5. Cao H and Zhang R (2019) Using PCA to improve the detection of medical insurance fraud in SOFM Neural Networks. In: 2019 3rd International Conference on Management Engineering, Software Engineering and Service Sciences. Association for Computing Machinery, New York, NY, USA, pp 117–122

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