Cyber-Physical Systems Integration in Healthcare: AI-Enabled Decision Support Systems

Authors

  • Archana Das Department of Information Science and Engineering, New Horizon College of Engineering, Bangalore Author
  • S. Padmavathy Department of computer science and engineering, Sona college of technology, Salem Author
  • Shilpa NS Department of Information Science and Engineering T John Institute of Technology, Bangalore Author
  • R. Nagendran Department of Computer science and Engineering, Sri Ramakrishna Institute of Technology, Coimbatore Author
  • P. T. Anitha Data Science, School of computing, Mohan Babu University, Tirupathi Author
  • G. Nagalalli Department of ECE, Mahendra Engineering College Author
  • S. Alagumuthukrishnan Department of Computer Science and Engineering, CMR Institute of Technology, Hyderabad Telangana, India Author

DOI:

https://doi.org/10.56294/hl2025659

Keywords:

Cyber, Physical System, Integration, Healthcare, Decision, Support Systems, Artificial Intelligence, Intrusion, Quantum, Predictive, Detection System

Abstract

Abstract structured in: The convergence of Cyber-Physical Systems (CPS) and healthcare is bringing about a transformation in the delivery of patient care by bridging the gap between the digital and physical realms. By utilizing modern technologies, these systems make it possible to make intelligent decisions and gain insights that are driven by data in real time.
Introduction: The complexity of data integration, the mitigation of sophisticated cyber threats, and the guaranteeing of system scalability within a variety of healthcare infrastructures are among the most significant obstacles. 
Methods: This research presents the Artificial Intelligence-Enabled Intrusion Quantum Predictive Detection System (AI-IQPDS), an innovative approach that is intended to improve the operational reliability of healthcare CPS, as well as the security and predictive analytics capabilities of the system. AI-IQPDS combine quantum computing and machine learning to provide accurate intrusion detection and predictive decision assistance. Intelligent patient monitoring systems powered by AI can optimize hospital resource management, transmit data securely between connected devices, and detect emergencies early working. 
Results: Simulation results show that the system outperforms modern techniques in terms of precision of detection, speed of processing, and reduction of false-positives. The results of this research demonstrate the revolutionary possibilities of using CPS driven by AI in healthcare. 
Conclusion: Healthcare ecosystems that are both intelligent and scalable may be possible as a result of this integration, which might lead to better efficiency, security, and patient outcomes.

 

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Published

2025-06-04

How to Cite

1.
Das A, Padmavathy S, Shilpa NS, R N, Anitha PT, G N, et al. Cyber-Physical Systems Integration in Healthcare: AI-Enabled Decision Support Systems. Health Leadership and Quality of Life [Internet]. 2025 Jun. 4 [cited 2025 Jul. 1];4:659. Available from: https://hl.ageditor.ar/index.php/hl/article/view/659