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Deep Learning in Neuroradiology: A Systematic Review of Current Algorithms and Approaches for the New Wave of Imaging Technology
100
Zitationen
4
Autoren
2020
Jahr
Abstract
Although deep learning has demonstrated potential for each of these modalities, this review highlights several needs in the field of deep learning research including use of internal datasets without external validation, unavailability of implementation methods, inconsistent assessment metrics, and lack of clinical validation. However, the rapid growth of deep learning in neuroradiology holds promise and, as strides are made to improve standardization, generalizability, and reproducibility, it may soon play a role in clinical diagnosis and treatment of neurologic disorders.<i>Supplemental material is available for this article.</i>© RSNA, 2020.
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