Machine learning models trained on synthetic datasets of multiple sample sizes for the use of predicting blood pressure from clinical data in a national dataset.
<h4>Introduction</h4>The potential for synthetic data to act as a replacement for real data in research has attracted attention in recent months due to the prospect of increasing access to data and overcoming data privacy concerns when sharing data. The field of generative artificial int...
| Published in: | PLoS ONE |
|---|---|
| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2023-01-01
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| Online Access: | https://doi.org/10.1371/journal.pone.0283094 |