Unbiased identification of novel subclinical imaging biomarkers using unsupervised deep learning
Unbiased identification of novel subclinical imaging biomarkers using unsupervised deep learning
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London: Nature Publishing Group UK
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English
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Publisher
London: Nature Publishing Group UK
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Artificial intelligence has recently made a disruptive impact in medical imaging by successfully automatizing expert-level diagnostic tasks. However, replicating human-made decisions may inherently be biased by the fallible and dogmatic nature of human experts, in addition to requiring prohibitive amounts of training data. In this paper, we introdu...
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Unbiased identification of novel subclinical imaging biomarkers using unsupervised deep learning
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TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7395081
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7395081
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ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-020-69814-1
