De-Identifying Clinical Data for AI: A Technical and Regulatory Guide Patient data is fundamental to developing and training AI systems across many areas of healthcare and biomedical research. However, to protect patient privacy, it is necessary to remove sensitive information such as names, contact details, and dates before using the data to train AI models. De-identification is one of the most c...