A robust and interpretable ensemble machine learning model for predicting healthcare insurance fraud

A robust and interpretable ensemble machine learning model for predicting healthcare insurance fraud

Abstract Healthcare insurance fraud imposes a significant financial burden on healthcare systems worldwide, with annual losses reaching billions of dollars. This study aims to improve fraud detection accuracy using machine learning techniques. Our approach consists of three key stages: data preproce...

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Bibliographic Details
Main Authors: Zeyu Wang, Xiaofang Chen, Yiwei Wu, Linke Jiang, Shiming Lin, Gang Qiu
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Healthcare insurance fraud
Machine learning
Model ensemble
Model interpretability
Online Access:https://doi.org/10.1038/s41598-024-82062-x
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