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On the Interpretability of Artificial Intelligence in Radiology: Challenges and Opportunities

As artificial intelligence (AI) systems begin to make their way into clinical radiology practice, it is crucial to assure that they function correctly and that they gain the trust of experts. Toward this goal, approaches to make AI “interpretable” have gained attention to enhance the understanding o...

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Detalhes bibliográficos
Publicado no:Radiol Artif Intell
Main Authors: Reyes, Mauricio, Meier, Raphael, Pereira, Sérgio, Silva, Carlos A., Dahlweid, Fried-Michael, von Tengg-Kobligk, Hendrik, Summers, Ronald M., Wiest, Roland
Formato: Artigo
Idioma:Inglês
Publicado em: Radiological Society of North America 2020
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7259808/
https://ncbi.nlm.nih.gov/pubmed/32510054
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1148/ryai.2020190043
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