| # 🧠 DermaVLM Organization |
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| **DermaVLM** is an open-source research organization focused on **resource-efficient medical Vision–Language Models (VLMs) for medicine (our use case is dermatology)**. |
| Our work combines **synthetic data generation**, **LLM/VLM training**, **model inference**, and **clinical image annotation tools** into a unified research ecosystem. |
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| This organization is built around the **SCALEMED framework**, enabling scalable and cost-effective dermatology-focused AI research. |
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| You can reach main codes at https://github.com/DermaVLM |
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| ## 🧪 Research Foundation |
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| > **📄 Research Paper** |
| > This organization is part of the SCALEMED framework. |
| > **Read our paper on medRxiv**: |
| > **Resource-efficient medical vision language model for dermatology via a synthetic data generation framework** |
| > https://www.medrxiv.org/content/10.1101/2025.05.17.25327785v2 |
| > |
| > If you use any of our repositories in your research, please cite our paper (see the [Citation](#-citation) section). |
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| ## 📖 Citation |
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| If you use this organization or any associated repositories in your research, please cite: |
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| ```bibtex |
| @article{yilmaz2025resource, |
| title={Resource-efficient medical vision language model for dermatology via a synthetic data generation framework}, |
| author={Yilmaz, A and Yuceyalcin, F and Varol, R and Gokyayla, E and Erdem, O and Choi, D and Demircali, AA and Gencoglan, G and Posma, JM and Temelkuran, B}, |
| year={2025} |
| } |
| ``` |
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| Feel free to explore the repositories, open issues, or contribute to advancing medical-focused small and succesful vision-language models. |
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