| # 🧠 DermaVLM Organization | |
| **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. | |
| This organization is built around the **SCALEMED framework**, enabling scalable and cost-effective dermatology-focused AI research. | |
| You can reach main codes at https://github.com/DermaVLM | |
| ## 🧪 Research Foundation | |
| > **📄 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). | |
| ## 📖 Citation | |
| If you use this organization or any associated repositories in your research, please cite: | |
| ```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} | |
| } | |
| ``` | |
| Feel free to explore the repositories, open issues, or contribute to advancing medical-focused small and succesful vision-language models. | |