Expert-augmented machine learning
Expert-augmented machine learning
About this item
Full title
Author / Creator
Publisher
United States: National Academy of Sciences
Journal title
Language
English
Formats
Publication information
Publisher
United States: National Academy of Sciences
Subjects
More information
Scope and Contents
Contents
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 whether a certain task should be performed by a compute...
Alternative Titles
Full title
Expert-augmented machine learning
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7060733
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7060733
Other Identifiers
ISSN
0027-8424
E-ISSN
1091-6490
DOI
10.1073/pnas.1906831117
