Web: http://arxiv.org/abs/2010.00747

Sept. 21, 2022, 1:14 a.m. | Yuhao Zhang, Hang Jiang, Yasuhide Miura, Christopher D. Manning, Curtis P. Langlotz

cs.CL updates on arXiv.org arxiv.org

Learning visual representations of medical images (e.g., X-rays) is core to
medical image understanding but its progress has been held back by the scarcity
of human annotations. Existing work commonly relies on fine-tuning weights
transferred from ImageNet pretraining, which is suboptimal due to drastically
different image characteristics, or rule-based label extraction from the
textual report data paired with medical images, which is inaccurate and hard to
generalize. Meanwhile, several recent studies show exciting results from
unsupervised contrastive learning from natural …

arxiv images medical text

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