Published May 31, 2025 | Version v1

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

  • 1. Creospan, Chicago, United State of America.
  • 2. The University of West Georgia, Department of Business Administration, Athens, Georgia, United State of America.
  • 3. Southern University A & M College, Department of Computer Science Baton Rouge, Louisiana Institute, United State of America.

Description

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.

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