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Synthetic data is increasingly being used across the financial services, clinical research, manufacturing and transport industries. In clinical research, use cases for synthetic data include secondary analysis to identify novel treatment pathways, to develop healthcare policies, to evaluate research methods and, importantly, to evaluate research hypotheses without exposing real patients to potentially harmful experimental treatments. Methods for creating synthetic data in a manner that can reconcile the privacy of clinical trial participants while preserving the utility of data for analysis are rapidly evolving. However, challenges remain that include obtaining appropriate consent for the use of real patient data in the creation of synthetic datasets, eliminating bias in synthetic data and ensuring that data privacy concerns can be addressed.
Shalini Dwivedi (Sat,) studied this question.
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