What even is differential privacy?

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Medical imaging is currently undergoing a computational and machine learning-driven revolution. The advent of data-driven methods and generative artificial intelligence (AI) is set to transform diagnostics and patient care. These technologies, powered mostly by deep learning, have the potential to identify pathologies from medical images with unprecedented accuracy, provided they have access to massive, diverse datasets for training. Currently, however, the scarcity and sensitivity of medical data are impeding the collection of such diverse, large-scale datasets. Further, the sharing and storage of such data are tightly regulated in many jurisdictions to ascertain informational self-determination and protect patient privacy. The tension between leveraging data for scientific advances and protecting individual privacy rights is at the heart of current debates in data security and privacy.

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