Privacy-preserving computation methods encompass a range of techniques designed to analyze data without compromising the privacy of individuals. These methods are particularly important in epidemiological studies where personal health information is involved. The main goal is to enable researchers to extract useful insights from the data while ensuring that the data cannot be traced back to any individual.
