The Framing of machine learning risk prediction models illustrated by evaluation of sepsis in general wards
Abstract Problem framing is critical to developing risk prediction models because all subsequent development work and evaluation takes place within the context of how a problem has been framed and explicit documentation of framing choices makes it easier to compare evaluation metrics between publish...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-11-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-021-00529-x |