Prediction of tuberculosis using an automated machine learning platform for models trained on synthetic data
High-quality medical data is critical to the development and implementation of machine learning (ML) algorithms in healthcare; however, security, and privacy concerns continue to limit access. We sought to determine the utility of "synthetic data" in training ML algorithms for the detectio...
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Main Authors: | , , , , , , , , , |
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Format: | Book |
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Elsevier,
2022-01-01T00:00:00Z.
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Internet
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A1234.567 |
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Copy 1 | Available |