International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 03 | Mar 2025
p-ISSN: 2395-0072
www.irjet.net
Ensuring Resilient Healthcare Systems: Predictive Failure Detection and Automation in Critical U.S. Health Infrastructure Vijaybhasker Pagidoju, Saint Charles, MO USA Lead Site Reliability Engineer /Architect, Centene Corporation USA -------------------------------------------------------------------------***-----------------------------------------------------------------------ABSTRACT: Healthcare cybersecurity is seeing a revolution as the Artificial Intelligence (AI) is being integrated into it
and that is to protect hospitals, insurers, and other public health networks of digital attacks. The sophisticated cyberattacks of today emphasize the implementation of the real-time threat detection, anomaly prediction and its automated response systems which are possible with AI driven security mechanisms. Analysing AI’s role in strengthening national health infrastructure through AI’s capabilities like predictive analytics, encryption and compliance with regulation such as HIPAA and HITECH as the focus of this paper. In addition, it explains the problem of AI adoption, such as the privacy issues and adversarial attacks. Healthcare systems can provide more secure security, reduce the loss of service time, and protect the confidentiality of patient data to a greater degree by adopting a national cyber resilience framework based on AI.
KEYWORDS: Healthcare Automation, Predictive Monitoring, Fail Detection, Self-Healing systems, Cloud Healthcare, Large Language Models (LLMs), Chat GPT in Healthcare IT, System Reliability, Healthcare Cybersecurity, and Healthcare Cybersecurity.
I.INTRODUCTION The impact of the digital transformation of healthcare has been digital transformation of healthcare, improving patient care, improving operational efficiency, and making healthcare more accessible. While it has also attracted an ever-rising number of cyber threats against healthcare systems, including ransomware, data breaches, and phishing attacks. The continuous evolving threats have rendered the traditional security measures ineffective to battle them. Healthcare infrastructure is now strongly safeguarded with the help of AI as it has enabled a level of advanced threat detection, real time security monitoring and automated incident response. Toward this end, this paper studies how AI can be leveraged for cybersecurity within national health security, keeping data private, being electronically compliant, and being resilient from cyberattacks while addressing challenges around implementation.
Fig. 1 Predictive Analytics in Healthcare (Reveal BI, 2025)
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