Pre-trained multi-modal vision-language models (VLMs) are becoming
incre...
Medical data poses a daunting challenge for AI algorithms: it exists in ...
Pretraining on large natural image classification datasets such as Image...
Given the prevalence of 3D medical imaging technologies such as MRI and ...
Recent multi-modal contrastive learning models have demonstrated the abi...
Parameter-efficient methods (like Prompt or Adapters) for adapting
pre-t...
Much literature has shown that prompt-based learning is an efficient met...
Despite the routine use of electronic health record (EHR) data by
radiol...
FDG PET/CT imaging is a resource intensive examination critical for mana...
Background: In medical imaging, prior studies have demonstrated disparat...
Reproducibility of computational studies is a hallmark of scientific
met...