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CONTRASTIVE LEARNING OF MEDICAL VISUAL REPRESENTATIONS FROM PAIRED IMAGES AND TEXT

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Yuhao Zhang: 👋 Excited to share our latest work "Contrastive Learning of Medical Visual Representations from Paired Images and Text". We propose a contrastive framework for learning visual representations of medical images from paired textual data. arXiv: https://arxiv.org/abs/2010.00747 👇 (1/7) https://t.co/tuyA12iwoY

10 replies, 347 likes


Curt Langlotz: Hot off the press: We have developed a self-supervised learning method that is much better for pre-training than ImageNet--reduces labeling needs by an order of magnitude for medical imaging applications: @stanfordAIMI @Radiology_AI

4 replies, 183 likes


Peng Qi: Can you teach ConvNets to better find anomalies in medical images via "reading" the radiology report they are associated with? Yuhao Zhang's (@yuhaozhangx) new work shows how unsupervised learning on data that's already routinely collected in hospitals is surprisingly effective!

0 replies, 39 likes


Stanford NLP Group: Current medical image understanding suffers from weakness of vision-only pretraining or smallness of expert-labeled datasets. But our ConVIRT method exploits the text reports doctors already produce. By @yuhaozhangx @hjian42 Miura @chrmanning @curtlanglotz https://arxiv.org/abs/2010.00747 https://t.co/WpIE5DGJJl

0 replies, 32 likes


Yuhao Zhang: 🚀 Joint work with great collaborators @hjian42, Yasuhide Miura, @chrmanning & @curtlanglotz. Work at @stanfordnlp & @StanfordAIMI. ConVIRT = Contrasive VIsual Representation learning from Text 📖 Details in paper: https://arxiv.org/abs/2010.00747 Code is coming! (7/7)

1 replies, 5 likes


akira: https://arxiv.org/abs/2010.00747 This is a research for representation learning of a pair of medical images and text data by contrastive learning, which is commonly used in medical routine work. It is more useful than ImageNet-trained models and greatly improves on image retrievals.

0 replies, 2 likes


ワクワクさん: EBM is all you need!

0 replies, 1 likes


Hang Jiang: Take a look at our new work @stanfordnlp!

0 replies, 1 likes


Content

Found on Oct 05 2020 at https://arxiv.org/pdf/2010.00747.pdf

PDF content of a computer science paper: CONTRASTIVE LEARNING OF MEDICAL VISUAL REPRESENTATIONS FROM PAIRED IMAGES AND TEXT