68 citations · 82 across the 5 of their papers we have counts for
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cs.LG2023
LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype
Vivek Shankar, Xiaoli Yang, Vrishab Krishna +10
The accurate classification of lymphoma subtypes using hematoxylin and eosin (H&E)-stained tissue is complicated by the wide range of morphological features these cancers can exhib…
cs.CV2023
How to Train Your CheXDragon: Training Chest X-Ray Models for Transfer to Novel Tasks and Healthcare Systems
Cara Van Uden, Jeremy Irvin, Mars Huang +4
Self-supervised learning (SSL) enables label efficient training for machine learning models. This is essential for domains such as medical imaging, where labels are costly and time…