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A method for machine learning generation of realistic synthetic datasets for validating healthcare

Digital health applications can improve quality and effectiveness of healthcare, by offering a number

of new tools to users, which are often considered a medical device. Assuring their safe operation

requires, amongst others, clinical validation, needing large datasets to test them in realistic clinical

scenarios. Access to datasets is challenging, due to patient privacy concerns. Development of

synthetic datasets is seen as a potential alternative


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