Adaptive AI and quantum computing for real-time financial fraud detection and cyber-attack prevention in U.S. healthcare
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.
Institutions
- Southern University and Agricultural and Mechanical College (US)
- University of Georgia (US)
- Georgia State University (US)
- Chicago State University (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-05-31
- DOI
- https://doi.org/10.5281/zenodo.17337580
- Primary Topic
- Organizational and Employee Performance
- Type
- article
- Field-Weighted Citation Impact
- 0.00