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...

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Detalhes bibliográficos
Publicado no:Proc Natl Acad Sci U S A
Main Authors: Gennatas, Efstathios D., Friedman, Jerome H., Ungar, Lyle H., Pirracchio, Romain, Eaton, Eric, Reichmann, Lara G., Interian, Yannet, Luna, José Marcio, Simone, Charles B., Auerbach, Andrew, Delgado, Elier, van der Laan, Mark J., Solberg, Timothy D., Valdes, Gilmer
Formato: Artigo
Idioma:Inglês
Publicado em: National Academy of Sciences 2020
Assuntos:
Physical Sciences
Acesso em linha: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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