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Generative Adversarial Network Based Synthetic Learning and a Novel Domain Relevant Loss Term for Spine Radiographs
We further demonstrate the success of synthetic learning for the spine domain with a downstream clinical classification task (AUC of 0. 830 using synthetic data compared to AUC of 0. 886 using the real data).
Understanding Transfer Learning for Chest Radiograph Clinical Report Generation with Modified Transformer Architectures
In this paper we demonstrate the importance of domain specific pre-training and propose a modified transformer architecture for the medical image captioning task.
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