Abstract
With the continuous development of the medical insurance system and the continuous increase in the number of insured persons, medical insurance fraud has also intensified. Traditional fraud detection methods are no longer suitable for the needs of medical insurance fraud review. Aiming at the problem of drug reselling in medical insurance fraud, this paper uses the proximity matrix of the isolated forest to improve the LDOF algorithm, and proposes a new medical insurance medication anomaly detection algorithm. Through comparative experiments, our algorithm not only improves the accuracy of LDOF, but also improves the computational efficiency, and shows good performance in the application of actual medical insurance data sets.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
