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- ---
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- license: cc-by-4.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ pipeline_tag: any-to-any
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+ ---
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+ # Model Card for UniMedVL
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+ UniMedVL is the first unified medical foundation model for seamless multimodal understanding and generation, following a clinically-inspired Observation-Knowledge-Analysis framework.
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+ <div align="center">
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+ <img src="./assets/teaser.png" width="95%"/>
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+ </div>
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+ ## Model Details
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+ ### Model Description
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+ UniMedVL unifies medical multimodal understanding and generation within a single 14B-parameter architecture. The model supports visual question answering, medical report generation, text-to-medical-image synthesis, cross-modal translation, and virtual staining across 9 imaging modalities (CXR, CT, MRI, Ultrasound, Histopathology, Retinal Fundus, OCT, Endoscopy, and Dermoscopy).
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+ - **Developed by:** [Anonymous - Under Review]
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+ - **Model type:** Unified Vision-Language Model
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+ - **Language(s):** English (medical domain)
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+ - **License:** Apache License 2.0
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+ - **Model Size:** 14B parameters
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+
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+ ### Model Sources
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+ - **Repository:** https://github.com/[repository_name] (Under Construction)
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+ - **Project Page:** https://uni-medical.github.io/UniMedVL_Web/
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+ - **Paper:** https://arxiv.org/abs/xxxxx (Under Construction)
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+ - **Model Checkpoints:** Under Construction - Will be released soon
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+
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+ ## Uses
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+ ### Direct Use
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+ The model can be directly used for:
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+ - **Medical Visual Question Answering**: Answer clinical questions about medical images
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+ - **Medical Report Generation**: Generate radiology reports from medical images
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+ - **Text-to-Medical-Image Synthesis**: Generate medical images from textual descriptions
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+ - **Cross-Modal Translation**: Convert between different medical imaging modalities
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+ - **Virtual Staining**: Transform H&E images to IHC staining
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+ ### Out-of-Scope Use
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+ - **Clinical Decision Making**: This model is for research purposes only and should NOT be used for actual clinical diagnosis or treatment decisions
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