5 papers
Towards Autonomous and Auditable Medical Imaging Model Development
Shengyuan Liu, Jia-Xuan Jiang, Boyun Zheng +8
Large language model (LLM) agents are beginning to automate machine learning engineering (MLE) by coupling planning, code execution, debugging, and empirical feedback. Translating…
Radiology Report Generation for Low-Quality X-Ray Images
Hongze Zhu, Chen Hu, Jiaxuan Jiang +6
Vision-Language Models (VLMs) have significantly advanced automated Radiology Report Generation (RRG). However, existing methods implicitly assume high-quality inputs, overlooking…
Vision-Language Semantic Aggregation Leveraging Foundation Model for Generalizable Medical Image Segmentation
Wenjun Yu, Yinchen Zhou, Jia-Xuan Jiang +3
Multimodal models have achieved remarkable success in natural image segmentation, yet they often underperform when applied to the medical domain. Through extensive study, we attrib…
Single Domain Generalization for Multimodal Cross-Cancer Prognosis via Dirac Rebalancer and Distribution Entanglement
Jia-Xuan Jiang, Jiashuai Liu, Hongtao Wu +4
Deep learning has shown remarkable performance in integrating multimodal data for survival prediction. However, existing multimodal methods mainly focus on single cancer types and…
MFM-DA: Instance-Aware Adaptor and Hierarchical Alignment for Efficient Domain Adaptation in Medical Foundation Models
Jia-Xuan Jiang, Wenhui Lei, Yifeng Wu +5
Medical Foundation Models (MFMs), trained on large-scale datasets, have demonstrated superior performance across various tasks. However, these models still struggle with domain gap…