Computer ScienceJMIR Medical Informatics
Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing
D. Rankin, M. Black, et al.
This study, conducted by Debbie Rankin, Michaela Black, Raymond Bond, Jonathan Wallace, Maurice Mulvenna, and Gorka Epelde, reveals insights about the performance of machine learning models trained on synthetic healthcare data. It shows that while synthetic data can be useful, real data still holds a significant edge in accuracy, particularly with tree-based models. The research underlines the balance between privacy and data utility.
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