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Expert-augmented machine learning
Machine learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption is limited by the level of trust afforded by given models. Human vs. machine performance is commonly compared empirically to decide wheth...
Αποθηκεύτηκε σε:
| Τόπος έκδοσης: | Proc Natl Acad Sci U S A |
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| Κύριοι συγγραφείς: | , , , , , , , , , , , , , |
| Μορφή: | Artigo |
| Γλώσσα: | Inglês |
| Έκδοση: |
National Academy of Sciences
2020
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| Θέματα: | |
| Διαθέσιμο Online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7060733/ https://ncbi.nlm.nih.gov/pubmed/32071251 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.1906831117 |
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