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Sample-efficient learning with auxiliary class-label information
Building classification models from clinical data collected for past patients often requires additional example labeling and annotation by a human expert. Since example labeling may require to review a complete electronic health record the process can be very time consuming and costly. To make the p...
Uloženo v:
| Hlavní autoři: | , , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
American Medical Informatics Association
2011
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3243278/ https://ncbi.nlm.nih.gov/pubmed/22195160 |
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