Subpopulation-specific machine learning prognosis for underrepresented patients with double prioritized bias correction
Afrose, Song et al. highlight deficiencies in the widely accepted one-machine-learning-model-fits-all approach. The authors develop a bias correction method that produces specialized machine learning-based prognostication models for underrepresented racial and age groups.
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-09-01
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| Series: | Communications Medicine |
| Online Access: | https://doi.org/10.1038/s43856-022-00165-w |