Clinical AI is software that supports diagnosis, triage, or treatment decisions in healthcare. It may summarize patient records, flag risk, recommend tests, or rank cases for a clinician to review. In practice, it is decision-support technology: it can inform care, but it should not replace professional judgment.
For cyber security, Clinical AI matters because it handles highly sensitive data and can influence real-world outcomes. Attackers may target its training data, input pipeline, or model weights to poison results, bias recommendations, or cause unsafe advice. They may also steal patient data through poor access controls or extract model behavior through repeated queries. Defenders reduce these risks with strong authentication, encryption, audit logs, validation of model outputs, segmentation, and human oversight. In security reviews, the key question is not only whether the system works, but whether its outputs are trustworthy, traceable, and resilient to tampering.