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Adaptive AI and quantum computing for real-time financial fraud detection and cyber-attack prevention in U.S. healthcare

Year: 2025

Type: article

Abstract: This article explores the integration of adaptive AI and quantum computing to combat financial fraud and cyber-attacks in the U.S. healthcare sector. By leveraging deep neural networks, reinforcement learning, and quantum-enhanced models, we propose a hybrid framework capable of achieving high fraud detection accuracy and anomaly detection in real-time. Case studies and empirical evaluations demonstrate the superiority of the framework over traditional methods, while ethical and regulatory implications are addressed to ensure responsible deployment.

Source: World Journal of Advanced Research and Reviews

DOI: 10.5281/zenodo.17337579

Authors: Mukasa, Alex Lwembawo, Makandah, Esther A, Anwansedo, Sunday

Institutions: University of West Georgia, Southern University and Agricultural and Mechanical College

Language: English

Topic: Imbalanced Data Classification Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W7090459485

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