Histopathological diagnosis is a medical diagnosis made by examining tissue samples under a microscope. In modern workflows, those slides are often scanned into high-resolution digital images and reviewed with software that can highlight patterns, measure features, or assist with triage. The goal is to identify disease from the structure and appearance of cells and tissue.
In cyber security, this term matters because digital pathology is a high-trust environment: image integrity, patient privacy, and model reliability all affect clinical decisions. Attackers may try to tamper with slide images, poison training data for AI-assisted diagnosis, or disrupt systems with ransomware so specimens cannot be reviewed. Defenders therefore focus on secure storage, access control, audit logs, backup, and validation of AI outputs against expert review. When histopathological diagnosis is supported by software, security and quality controls are part of patient safety.