4 citations · 9 across the 14 of their papers we have counts for
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cs.CV2024★ 4 cited
FairMedFM: Fairness Benchmarking for Medical Imaging Foundation Models
Ruinan Jin, Zikang Xu, Yuan Zhong +4
The advent of foundation models (FMs) in healthcare offers unprecedented opportunities to enhance medical diagnostics through automated classification and segmentation tasks. Howev…
cs.CV2024
Debiased Noise Editing on Foundation Models for Fair Medical Image Classification
Ruinan Jin, Wenlong Deng, Minghui Chen +1
In the era of Foundation Models' (FMs) rising prominence in AI, our study addresses the challenge of biases in medical images while the model operates in black-box (e.g., using FM…
cs.CV2024★ 1 cited
Backdoor Attack on Unpaired Medical Image-Text Foundation Models: A Pilot Study on MedCLIP
Ruinan Jin, Chun-Yin Huang, Chenyu You +1
In recent years, foundation models (FMs) have solidified their role as cornerstone advancements in the deep learning domain. By extracting intricate patterns from vast datasets, th…