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cs.CV2026
MedPMC: A Systematic Framework for Scaling High-Fidelity Medical Multimodal Data for Foundation Models
Hyunjae Kim, Dain Kim, Pan Xiao +25
Medicine is inherently multimodal, requiring clinicians to synthesize information across diverse data streams. Yet the development of multimodal foundation models is constrained by…
cs.CV2026
VOLMO: Versatile and Open Large Models for Ophthalmology
Zhenyue Qin, Younjoon Chung, Elijah Lee +16
Vision impairment affects millions globally, and early detection is critical to preventing irreversible vision loss. Ophthalmology workflows require clinicians to integrate medical…
cs.CV2025
From Compound Figures to Medical Multi-image Reasoning: Scaling Multimodal Large Language Models with Biomedical Literature
Zhen Chen, Yihang Fu, Rong Zhou +12
Multimodal large language models (MLLMs) are increasingly capable in medical imaging, yet most focus on single-image settings. Clinical interpretation often requires integrating ev…