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The advancements promised by AI enabled healthcare have inherent vulnerability aspects concerning patient privacy and adoption of timely cybersecurity measures to protect sensitive healthcare data. AI algorithms for threat detection, anomaly detection, and predictive analytics, healthcare organisations are very useful in identification and mitigation of security threats. This results in least disruption in patient care regime and therefore ensures the confidentiality of patient information. This chapter is aimed to provide discussions on potential impact of AI-enabled healthcare security on patient outcomes. The chapter also provides insights into good case studies of hospitals and organizations who have successfully deployed AI to manage patient centric AI-enabled healthcare security solutions.

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Impact of AI-Enabled Healthcare Security on Patient Outcomes

  • 章节

  • 发表日期：

    2025年

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  • Sunil Gupta,
  • Monit Kapoor,
  • Sanjoy Kumar Debnath

摘要

The advancements promised by AI enabled healthcare have inherent vulnerability aspects concerning patient privacy and adoption of timely cybersecurity measures to protect sensitive healthcare data. AI algorithms for threat detection, anomaly detection, and predictive analytics, healthcare organisations are very useful in identification and mitigation of security threats. This results in least disruption in patient care regime and therefore ensures the confidentiality of patient information. This chapter is aimed to provide discussions on potential impact of AI-enabled healthcare security on patient outcomes. The chapter also provides insights into good case studies of hospitals and organizations who have successfully deployed AI to manage patient centric AI-enabled healthcare security solutions.