Precision medicine is a care model that tailors treatment to the individual instead of applying the same plan to everyone. It uses patient-specific data such as genetics, imaging, lab results, and medical history to guide diagnosis, drug choice, and dosage. In AI-enabled healthcare, this makes the quality of data and model outputs especially important: a small error can lead to the wrong recommendation for a specific patient.
From a cyber-security perspective, precision medicine depends on protecting confidentiality, integrity, and availability. Attackers may try to steal sensitive health data, alter records or model inputs, or disrupt clinical systems with ransomware. Defenders need strong access control, encryption, logging, secure data provenance, and model validation so that personalized recommendations can be trusted. In practice, precision medicine works best when human review, clean data, and security controls are built into the workflow.