5 citations · 5 across the 3 of their papers we have counts for
4 papers
Improving Learning of New Diseases through Knowledge-Enhanced Initialization for Federated Adapter Tuning
Danni Peng, Yuan Wang, Kangning Cai +6
In healthcare, federated learning (FL) is a widely adopted framework that enables privacy-preserving collaboration among medical institutions. With large foundation models (FMs) de…
EH-Benchmark Ophthalmic Hallucination Benchmark and Agent-Driven Top-Down Traceable Reasoning Workflow
Xiaoyu Pan, Yang Bai, Ke Zou +5
Medical Large Language Models (MLLMs) play a crucial role in ophthalmic diagnosis, holding significant potential to address vision-threatening diseases. However, their accuracy is…
Partially Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation
Lei Zhu, Yanyu Xu, Huazhu Fu +3
Unpaired Multi-Modal Learning (UMML) which leverages unpaired multi-modal data to boost model performance on each individual modality has attracted a lot of research interests in m…
Look Back for More: Harnessing Historical Sequential Updates for Personalized Federated Adapter Tuning
Danni Peng, Yuan Wang, Huazhu Fu +4
Personalized federated learning (PFL) studies effective model personalization to address the data heterogeneity issue among clients in traditional federated learning (FL). Existing…