arXiv:2606. 04613v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) struggle when applied to medical image-text data, yet the tools available to diagnose this failure remain limited.
By Alessandro Gambetti, Qiwei Han, Cl\'audia Soares, Hong Shen
arXiv:2608. 10316v1 Announce Type: cross Abstract: Multi-modal learning combining medical images and clinical text is promising for disease diagnosis.
By Zijian Gu, Weikai Lin, Shuang Zhou, Zihan Chen, Song Wang
arXiv:2606. 15038v1 Announce Type: new Abstract: Accurate time-to-event (TTE) prediction from multimodal clinical data remains challenging due to modality imbalance and distribution shift.
By Zhemin Zhang, Weijie Chen, David Le, Amara Tariq, Alex Wallace, Matthew Stib, Juan Maria Farina, Chadi Ayoub, Reza Arsanjani, Imon Banerjee
arXiv:2609.39266v1 Announce Type: new
Abstract: Fine-grained vision-language alignment in chest radiography enables zero-shot classification, grounding, and segmentation without task-specific annotat...
By Qixing Zhao, Jinpeng Li
arXiv:2608. 19825v1 Announce Type: cross Abstract: Medical image captioning is a technique that accelerates early-stage diagnostic workflows and enhances the interpretability of medical diagnostic AI systems.
By Yunseo Lee, Hyun Jun Kim, Heeseung Shin, Changwon Lim
arXiv:2608. 04472v1 Announce Type: cross Abstract: The development of foundation models (FMs) is crucial for advancing endoscopic image analysis.
By Zhenyu Yi, Jianwei Xu, Yue Hu, Zhongwei Qiu, Sijing Li, Liang Huang, Bin Lv, Ling Zhang, Yingda Xia