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Keeping Patient Data Secure in the Age of Radiology Artificial Intelligence: Cybersecurity Considerations and Future
Chintan Shah1, Douglas Nachand2, Christoph Wald3
1Associate Staff, Section of Neuroradiology and Section of Imaging Informatics, Safety, Improvement, Quality and Experience Officer-Neuroradiology, Department of Radiology, Imaging Institute, Cleveland Clinic, Cleveland, Ohio.
Abstract:
Artificial intelligence (AI)-based solutions are increasingly being incorporated into radiology workflows. Implementation of AI comes along with cybersecurity risks and challenges that practices should be aware of and mitigate for a successful and secure deployment. In this article, these cybersecurity issues are examined through the lens of the "CIA" triad framework-confidentiality, integrity, and availability. We discuss the implications of implementation configurations and development approaches on data security and confidentiality and the potential impact that the insertion of AI can have on the truthfulness of data, access to data, and the cybersecurity attack surface. Finally, we provide a checklist to address important security considerations before deployment of an AI application, and discuss future advances in AI addressing some of these security concerns.
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