A healthcare organization uses data clustering to group patients by medical history for personalized treatment recommendations. Which of the following is the GREATEST privacy risk associated with…

Requiring more data is not inherently a greater privacy risk; the risk depends on how data is protected and used, not the volume alone.

Increased model complexity does not directly make data harder to anonymize; anonymization techniques operate independently of model complexity.

Irrelevant features causing inaccurate or biased treatment recommendations is a data quality and model accuracy risk, not primarily a privacy risk.

Data clustering groups individuals by shared attributes, and the way clusters are labeled, described, or presented can reveal highly sensitive information about the individuals within them - such as mental health conditions, chronic illnesses, or substance use. Even if individual records are anonymized, cluster membership itself can act as a quasi-identifier, enabling re-identification or inference of sensitive conditions. This indirect disclosure risk is the greatest privacy threat inherent in clustering for healthcare applications.