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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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| Pubblicato in: | Radiol Artif Intell |
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| Autori principali: | , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Radiological Society of North America
2020
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| Soggetti: | |
| Accesso online: | 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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