Publications by authors named "Donato Zigrino"

Article Synopsis
  • - Medical image classification using convolutional neural networks (CNNs) usually needs a lot of manual adjustments, but neural architecture search (NAS) can automate this process, making it more efficient.
  • - This study focuses on classifying different sub-types of cardiac amyloidosis using NAS on [18F]-Florbetaben PET cardiac images, with a significant dataset augmentation from 597 to 4048 images, resulting in 5000 evaluated architectures.
  • - The best-performing network, named NAS-Net, achieved 76.95% overall accuracy and showed impressive sensitivity and specificity rates for the AL and ATTR-CA subjects, confirming that NAS can rival traditional methods while using fewer parameters.
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