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Unbiased identification of novel subclinical imaging biomarkers using unsupervised deep learning
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 a...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7395081/ https://www.ncbi.nlm.nih.gov/pubmed/32737379 http://dx.doi.org/10.1038/s41598-020-69814-1 |