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Abstract: Adversarial Examples as Benchmark for Medical Imaging Neural Networks
[chapter]
2019
Handbook of Experimental Pharmacology
Deep learning has been widely adopted as the solution of choice for a plethora of medical imaging applications, due to its state-of-the-art performance and fast deployment. Traditionally, the performance of a deep learning model is evaluated on a test dataset, originating from the same distribution as the training set. This evaluation method provides insight regarding the generalization ability of a model. However, in medical imaging scenarios, especially in cases when a deep learning framework
doi:10.1007/978-3-658-25326-4_4
fatcat:bch6xie7tfebdbereerp4dwwmu